Patent ID: 12213856

DETAILED DESCRIPTION

In general, described herein are methods and apparatuses for manufacturing a series of aligners for a patient's teeth that may include generating multiple treatment plans that are limited various specified stages (e.g., 5 stages, 6 stages, 7 stages, 8 stages, 9 stages, 10 stages, 10 stages, 12 stages, 14 stages, 15 stages, 16 stages, 17 stages, 18 stages, 19 stages, 20 stages, 21 stages, 22 stages, 23 stages, 24 stages, 25 stages, 26 stages, 27 stages, 28 stages, 29 stages, 30 stages, etc.) and variations of these fixed-stage treatment plans in which one or more features are included to a predetermined degree (e.g., interproximal reduction, use of some number of aligner attachments, etc.). These methods and apparatuses may also include interactively displaying the multiple treatment plans, and allowing a user, such as a dental professional (e.g., doctor, dentist, orthodontist, etc.) to view, select and/or modify the multiple treatment plans. The multiple treatment plans may be labeled to indicate what treatment goals they do or do not address. The user may also select a subset of the multiple treatment plans for inclusion as part of a patient consultation, displaying the treatment plans for comparison and selection by patient.

A treatment plan optimizing generator, described in greater detail below, may be used to generate a plurality of treatment plans that are variations of each other. Typically the input to the treatment plan optimizing generator is a digital scan of the patient's teeth, as well as the constraints (e.g., number of stages, tooth modifications features, etc.) and preferences, and an “ideal” alignment of the patient's teeth (which may be manually, automatically or semi-automatically generated). The treatment plan optimizing generator may then automatically generate a treatment plan that is limited by those constraints, and that both addresses one or more treatment goals (which may also be identified or automatically identified) and is as close to the ideal alignment as possible. The treatment plan optimizing generator may be used multiple times to automatically generate a plurality of treatment plan variations that may be collected into an array (or group) of treatment plans.

As will be described in greater detail here, the results of the multiple treatment plan generation may be presented to a user. The multiple treatment plans may be collected as an array of multiple treatment plans that may include metadata identifying each treatment plan and/or the treatment goal that it addresses or does not address. Each treatment plan may represent a clinically feasible treatment plan. Further, for each plan there may be several options available to modify the plan. Plans may be limited to the number of stages, which may correlate to a commercial product. The product may include restrictions (product limitations) which may be included in the treatment plan. For example treatment plans may correspond to low stage plans (e.g. between 5 and 13 stages), intermediate stage plans (between 14 and 25 stages) and high intermediate stage plans (26 and more stages). Other tooth modification features may also be included as limitations modifying the treatment plans, such as including or not including aligner attachment placement. If attachments are not allowed, then a restricted clinical protocol may be applied to avoid unpredictable movements. Another example of a tooth modification feature that may be included in the treatment plan is to include IPR or not include IPR. If IPR is not allowed then the best plan may be presented with a condition that IPR is not allowed during the duration of the treatment.

In addition, template selection may select a clinical protocol to be applied for plan generation. The user may select any combination of options in order to determine which treatment plan is the best, given the constraints provided. All possible combinations of the plans are pre-calculated so the user can see, in real time, the options available by changing to a different clinical filter without the need to redo the treatment plan. The user may also modify any of the treatment plans with 3D controls, in which each change made with tools modifies a plan but is configured to keeps the ability to transfer the selected (and modified) treatment plan directly to manufacturing (e.g., without further human intervention).

In general, the methods described here are directed to the manufacture of a series or sequence of orthodontic aligner appliances that maybe worn sequentially to correct malocclusion(s). For example,FIG.1illustrates an exemplary tooth repositioning appliance or aligner100that can be worn by a patient in order to achieve an incremental repositioning of individual teeth121in the jaw. The appliance can include a shell110(e.g., a continuous polymeric shell or a segmented shell) having teeth-receiving cavities111that receive and resiliently reposition the teeth121. An appliance or portion(s) thereof may be indirectly fabricated using a physical model of teeth. For example, an appliance (e.g., polymeric appliance) can be formed using a physical model of teeth and a sheet of suitable layers of polymeric material. In some embodiments, a physical appliance is directly fabricated, e.g., using additive manufacturing techniques, from a digital model of an appliance. An appliance can fit over all teeth present in an upper or lower jaw, or less than all of the teeth. The appliance can be designed specifically to accommodate the teeth of the patient (e.g., the topography of the tooth-receiving cavities matches the topography of the patient's teeth), and may be fabricated based on positive or negative models of the patient's teeth generated by impression, scanning, and the like. Alternatively, the appliance can be a generic appliance configured to receive the teeth, but not necessarily shaped to match the topography of the patient's teeth. In some cases, only certain teeth received by an appliance may be repositioned by the appliance while other teeth can provide a base or anchor region for holding the appliance in place as it applies force against the tooth or teeth targeted for repositioning. In some cases, some or most, and even all, of the teeth may be repositioned at some point during treatment. Teeth that are moved can also serve as a base or anchor for holding the appliance as it is worn by the patient. No wires or other means may be necessary for holding an appliance in place over the teeth. In some cases, however, it may be desirable or necessary to provide individual attachments or other aligner features for controlling force delivery and distribution Exemplary appliances, including those utilized in the Invisalign® System, are described in numerous patents and patent applications assigned to Align Technology, Inc. including, for example, in U.S. Pat. Nos. 6,450,807, and 5,975,893, as well as on the company's website, which is accessible on the World Wide Web (see, e.g., the url “invisalign.com”). Examples of tooth-mounted attachments suitable for use with orthodontic appliances are also described in patents and patent applications assigned to Align Technology, Inc., including, for example, U.S. Pat. Nos. 6,309,215 and 6,830,450.

Optionally, in cases involving more complex movements or treatment plans, it may be beneficial to utilize auxiliary components (e.g., features, accessories, structures, devices, components, and the like) in conjunction with an orthodontic appliance. Examples of such accessories include but are not limited to elastics, wires, springs, bars, arch expanders, palatal expanders, twin blocks, occlusal blocks, bite ramps, mandibular advancement splints, bite plates, pontics, hooks, brackets, headgear tubes, springs, bumper tubes, palatal bars, frameworks, pin-and-tube apparatuses, buccal shields, buccinator bows, wire shields, lingual flanges and pads, lip pads or bumpers, protrusions, divots, and the like. Additional examples of accessories include but are not limited to opposing arch features, occlusal features, torsional rigidity features, occlusal cusp, and bridges. In some embodiments, the appliances, systems and methods described herein include improved orthodontic appliances with integrally formed features that are shaped to couple to such auxiliary components, or that replace such auxiliary components.

FIG.1Billustrates a tooth repositioning system110including a plurality of appliances112,114,116. Any of the appliances described herein can be designed and/or provided as part of a set of a plurality of appliances used in a tooth repositioning system. Each appliance may be configured so a tooth-receiving cavity has a geometry corresponding to an intermediate or final tooth arrangement intended for the appliance. The patient's teeth can be progressively repositioned from an initial tooth arrangement towards a target tooth arrangement by placing a series of incremental position adjustment appliances over the patient's teeth. For example, the tooth repositioning system110can include a first appliance112corresponding to an initial tooth arrangement, one or more intermediate appliances114corresponding to one or more intermediate arrangements, and a final appliance116corresponding to a target arrangement. A target tooth arrangement can be a planned final tooth arrangement selected for the patient's teeth at the end of all planned orthodontic treatment. Alternatively, a target arrangement can be one of some intermediate arrangements for the patient's teeth during the course of orthodontic treatment, which may include various different treatment scenarios, including, but not limited to, instances where surgery is recommended, where interproximal reduction (IPR) is appropriate, where a progress check is scheduled, where anchor placement is best, where palatal expansion is desirable, where restorative dentistry is involved (e.g., inlays, onlays, crowns, bridges, implants, veneers, and the like), etc. As such, it is understood that a target tooth arrangement can be any planned resulting arrangement for the patient's teeth that follows one or more incremental repositioning stages. Likewise, an initial tooth arrangement can be any initial arrangement for the patient's teeth that is followed by one or more incremental repositioning stages.

FIG.1Cillustrates a method150of orthodontic treatment using a plurality of appliances, in accordance with embodiments. The method150can be practiced using any of the appliances or appliance sets described herein. In step160, a first orthodontic appliance is applied to a patient's teeth in order to reposition the teeth from a first tooth arrangement to a second tooth arrangement. In step170, a second orthodontic appliance is applied to the patient's teeth in order to reposition the teeth from the second tooth arrangement to a third tooth arrangement. The method150can be repeated as necessary using any suitable number and combination of sequential appliances in order to incrementally reposition the patient's teeth from an initial arrangement towards a target arrangement. The appliances can be generated all at the same stage or in sets or batches (e.g., at the beginning of a stage of the treatment), or the appliances can be fabricated one at a time, and the patient can wear each appliance until the pressure of each appliance on the teeth can no longer be felt or until the maximum amount of expressed tooth movement for that given stage has been achieved. A plurality of different appliances (e.g., a set) can be designed and even fabricated prior to the patient wearing any appliance of the plurality. After wearing an appliance for an appropriate period of time, the patient can replace the current appliance with the next appliance in the series until no more appliances remain. The appliances are generally not affixed to the teeth and the patient may place and replace the appliances at any time during the procedure (e.g., patient-removable appliances). The final appliance or several appliances in the series may have a geometry or geometries selected to overcorrect the tooth arrangement. For instance, one or more appliances may have a geometry that would (if fully achieved) move individual teeth beyond the tooth arrangement that has been selected as the “final.” Such over-correction may be desirable in order to offset potential relapse after the repositioning method has been terminated (e.g., permit movement of individual teeth back toward their pre-corrected positions). Over-correction may also be beneficial to speed the rate of correction (e.g., an appliance with a geometry that is positioned beyond a desired intermediate or final position may shift the individual teeth toward the position at a greater rate). In such cases, the use of an appliance can be terminated before the teeth reach the positions defined by the appliance. Furthermore, over-correction may be deliberately applied in order to compensate for any inaccuracies or limitations of the appliance.

The various embodiments of the orthodontic appliances presented herein can be fabricated in a wide variety of ways. In some embodiments, the orthodontic appliances herein (or portions thereof) can be produced using direct fabrication, such as additive manufacturing techniques (also referred to herein as “3D printing) or subtractive manufacturing techniques (e.g., milling). In some embodiments, direct fabrication involves forming an object (e.g., an orthodontic appliance or a portion thereof) without using a physical template (e.g., mold, mask etc.) to define the object geometry. For example, stereolithography can be used to directly fabricate one or more of the appliances herein. In some embodiments, stereolithography involves selective polymerization of a photosensitive resin (e.g., a photopolymer) according to a desired cross-sectional shape using light (e.g., ultraviolet light). The object geometry can be built up in a layer-by-layer fashion by sequentially polymerizing a plurality of object cross-sections. As another example, the appliances herein can be directly fabricated using selective laser sintering. In some embodiments, selective laser sintering involves using a laser beam to selectively melt and fuse a layer of powdered material according to a desired cross-sectional shape in order to build up the object geometry. As yet another example, the appliances herein can be directly fabricated by fused deposition modeling. In some embodiments, fused deposition modeling involves melting and selectively depositing a thin filament of thermoplastic polymer in a layer-by-layer manner in order to form an object. In yet another example, material jetting can be used to directly fabricate the appliances herein. In some embodiments, material jetting involves jetting or extruding one or more materials onto a build surface in order to form successive layers of the object geometry.

In some embodiments, the direct fabrication methods provided herein build up the object geometry in a layer-by-layer fashion, with successive layers being formed in discrete build steps. Alternatively or in combination, direct fabrication methods that allow for continuous build-up of an object's geometry can be used, referred to herein as “continuous direct fabrication.” Various types of continuous direct fabrication methods can be used. Continuous liquid interphase printing is described in U.S. Patent Publication Nos. 2015/0097315, 2015/0097316, and 2015/0102532, the disclosures of each of which are incorporated herein by reference in their entirety.

As another example, a continuous direct fabrication method can achieve continuous build-up of an object geometry by continuous movement of the build platform (e.g., along the vertical or Z-direction) during the irradiation phase, such that the hardening depth of the irradiated photopolymer is controlled by the movement speed. Accordingly, continuous polymerization of material on the build surface can be achieved. Such methods are described in U.S. Pat. No. 7,892,474, the disclosure of which is incorporated herein by reference in its entirety.

In another example, a continuous direct fabrication method can involve extruding a composite material composed of a curable liquid material surrounding a solid strand. The composite material can be extruded along a continuous three-dimensional path in order to form the object. Such methods are described in U.S. Patent Publication No. 2014/0061974, the disclosure of which is incorporated herein by reference in its entirety.

In yet another example, a continuous direct fabrication method utilizes a “heliolithography” approach in which the liquid photopolymer is cured with focused radiation while the build platform is continuously rotated and raised. Accordingly, the object geometry can be continuously built up along a spiral build path. Such methods are described in U.S. Patent Publication No. 2014/0265034, the disclosure of which is incorporated herein by reference in its entirety.

In some embodiments, relatively rigid portions of the orthodontic appliance can be formed via direct fabrication using one or more of the following materials: a polyester, a co-polyester, a polycarbonate, a thermoplastic polyurethane, a polypropylene, a polyethylene, a polypropylene and polyethylene copolymer, an acrylic, a cyclic block copolymer, a polyetheretherketone, a polyamide, a polyethylene terephthalate, a polybutylene terephthalate, a polyetherimide, a polyethersulfone, and/or a polytrimethylene terephthalate.

In some embodiments, relatively elastic portions of the orthodontic appliance can be formed via direct fabrication using one or more of the following materials: a styrenic block copolymer (SBC), a silicone rubber, an elastomeric alloy, a thermoplastic elastomer (TPE), a thermoplastic vulcanizate (TPV) elastomer, a polyurethane elastomer, a block copolymer elastomer, a polyolefin blend elastomer, a thermoplastic co-polyester elastomer, and/or a thermoplastic polyamide elastomer.

Optionally, the direct fabrication methods described herein allow for fabrication of an appliance including multiple materials, referred to herein as “multi-material direct fabrication.” In some embodiments, a multi-material direct fabrication method involves concurrently forming an object from multiple materials in a single manufacturing step using the same fabrication machine and method. For instance, a multi-tip extrusion apparatus can be used to selectively dispense multiple types of materials (e.g., resins, liquids, solids, or combinations thereof) from distinct material supply sources in order to fabricate an object from a plurality of different materials. Such methods are described in U.S. Pat. No. 6,749,414, the disclosure of which is incorporated herein by reference in its entirety. Alternatively or in combination, a multi-material direct fabrication method can involve forming an object from multiple materials in a plurality of sequential manufacturing steps. For instance, a first portion of the object can be formed from a first material in accordance with any of the direct fabrication methods herein, then a second portion of the object can be formed from a second material in accordance with methods herein, and so on, until the entirety of the object has been formed.

In many embodiments, post-processing of appliances includes cleaning, post-curing, and/or support removal processes. Relevant post-processing parameters can include purity of cleaning agent, cleaning pressure and/or temperature, cleaning time, post-curing energy and/or time, and/or consistency of support removal process. These parameters can be measured and adjusted as part of a process control scheme. In addition, appliance physical properties can be varied by modifying the post-processing parameters. Adjusting post-processing machine parameters can provide another way to compensate for variability in material properties and/or machine properties.

Although various embodiments herein are described with respect to direct fabrication techniques, it shall be appreciated that other techniques can also be used, such as indirect fabrication techniques. In some embodiments, the appliances herein (or portions thereof) can be produced using indirect fabrication techniques, such as by thermoforming over a positive or negative mold. Indirect fabrication of an orthodontic appliance can involve one or more of the following steps: producing a positive or negative mold of the patient's dentition in a target arrangement (e.g., by additive manufacturing, milling, etc.), thermoforming one or more sheets of material over the mold in order to generate an appliance shell, forming one or more structures in the shell (e.g., by cutting, etching, etc.), and/or coupling one or more components to the shell (e.g., by extrusion, additive manufacturing, spraying, thermoforming, adhesives, bonding, fasteners, etc.). Optionally, one or more auxiliary appliance components as described herein (e.g., elastics, wires, springs, bars, arch expanders, palatal expanders, twin blocks, occlusal blocks, bite ramps, mandibular advancement splints, bite plates, pontics, hooks, brackets, headgear tubes, bumper tubes, palatal bars, frameworks, pin-and-tube apparatuses, buccal shields, buccinator bows, wire shields, lingual flanges and pads, lip pads or bumpers, protrusions, divots, etc.) are formed separately from and coupled to the appliance shell (e.g., via adhesives, bonding, fasteners, mounting features, etc.) after the shell has been fabricated.

The orthodontic appliances herein can be fabricated using a combination of direct and indirect fabrication techniques, such that different portions of an appliance can be fabricated using different fabrication techniques and assembled in order to form the final appliance. For example, an appliance shell can be formed by indirect fabrication (e.g., thermoforming), and one or more structures or components as described herein (e.g., auxiliary components, power arms, etc.) can be added to the shell by direct fabrication (e.g., printing onto the shell).

The configuration of the orthodontic appliances herein can be determined according to a treatment plan for a patient, e.g., a treatment plan involving successive administration of a plurality of appliances for incrementally repositioning teeth. Computer-based treatment planning and/or appliance manufacturing methods can be used in order to facilitate the design and fabrication of appliances. For instance, one or more of the appliance components described herein can be digitally designed and fabricated with the aid of computer-controlled manufacturing devices (e.g., computer numerical control (CNC) milling, computer-controlled additive manufacturing such as 3D printing, etc.). The computer-based methods presented herein can improve the accuracy, flexibility, and convenience of appliance fabrication.

The methods and apparatuses described herein may form, or be incorporated into a computer-based 3-dimensional planning/design tool, and may be used to design and fabricate the orthodontic appliances described herein.

FIG.2Ashows one example of a treatment plan solver (e.g., an automated orthodontic treatment planning system, or solver)101that may be used to automatically generate a series of treatment plans and therefore manufacture a series of aligners based on one of the series of treatment plans.

The solver101may include a variety of modules, including engines, processors on which the engines may operate, and/or one or more datastores. A computer system can be implemented as an engine, as part of an engine or through multiple engines. As used herein, an engine may include one or more processors or a portion thereof. A portion of one or more processors can include some portion of hardware less than all of the hardware comprising any given one or more processors, such as a subset of registers, the portion of the processor dedicated to one or more threads of a multi-threaded processor, a time slice during which the processor is wholly or partially dedicated to carrying out part of the engine's functionality, or the like. As such, a first engine and a second engine can have one or more dedicated processors or a first engine and a second engine can share one or more processors with one another or other engines. Alternatively or additionally, different engines may share the same processor. Depending upon implementation-specific or other considerations, an engine can be centralized or its functionality distributed. An engine can include hardware, firmware, or software embodied in a computer-readable medium for execution by the processor. The processor transforms data into new data using implemented data structures and methods, such as is described with reference to the figures herein.

The engines described herein, or the engines through which the systems and devices described herein can be implemented, can be cloud-based engines. As used herein, a cloud-based engine is an engine that can run applications and/or functionalities using a cloud-based computing system. All or portions of the applications and/or functionalities can be distributed across multiple computing devices, and need not be restricted to only one computing device. In some embodiments, the cloud-based engines can execute functionalities and/or modules that end users access through a web browser or container application without having the functionalities and/or modules installed locally on the end-users' computing devices.

As used herein, datastores are intended to include repositories having any applicable organization of data, including tables, comma-separated values (CSV) files, traditional databases (e.g., SQL), or other applicable known or convenient organizational formats. Datastores can be implemented, for example, as software embodied in a physical computer-readable medium on a specific-purpose machine, in firmware, in hardware, in a combination thereof, or in an applicable known or convenient device or system. Datastore-associated components, such as database interfaces, can be considered “part of” a datastore, part of some other system component, or a combination thereof, though the physical location and other characteristics of datastore-associated components is not critical for an understanding of the techniques described herein.

Datastores can include data structures. As used herein, a data structure is associated with a particular way of storing and organizing data in a computer so that it can be used efficiently within a given context. Data structures are generally based on the ability of a computer to fetch and store data at any place in its memory, specified by an address, a bit string that can be itself stored in memory and manipulated by the program. Thus, some data structures are based on computing the addresses of data items with arithmetic operations; while other data structures are based on storing addresses of data items within the structure itself. Many data structures use both principles, sometimes combined in non-trivial ways. The implementation of a data structure usually entails writing a set of procedures that create and manipulate instances of that structure. The datastores, described herein, can be cloud-based datastores. A cloud-based datastore is a datastore that is compatible with cloud-based computing systems and engines.

InFIG.2Athe system for automatically creating an orthodontic treatment plan of a patient may include one or more processors102. The treatment plan solver set of instructions may operate on the one or more processors. The system may also include a collision detector106, which may also operate on the one or more processors. The system may also include a memory that is part of or coupled to the one or more processors, and which stores computer-program instructions, that, when executed by the one or more processors, perform a computer-implemented method that may include collecting (e.g., forming, reading, receiving, etc.) a digital model of a surface for each tooth of a plurality of a patient's teeth by packing a plurality of 3D shapes to approximate (e.g., model, form, etc.) the surface for each tooth, wherein the 3D shapes each have a core that is a line segment or a closed plane figure and an outer surface that is a constant radius from the core. As will be described in greater detail below, the collision detector106may include hardware, software and/or firmware for packing the tooth or other feature, and modeling the surface with the 3D shapes such as the capsules. The system may also be configured to collect (e.g., to receive, read, etc.) treatment preferences. The preferences may be collected into a treatment preference datastore115. The preferences may also include treatment details datastore117. The system may form, for the surface for each tooth of the plurality of the patient's teeth, a hierarchy of bounding boxes enclosing the plurality of 3D shapes. This may be performed using the processor and/or as part of the collision detector. The tooth positions for the plurality of the patient's teeth may be passed from a treatment plan solver101to a collision detector (see, e.g.,FIG.2B. The solver may collect a digital model of the patient's teeth to be modified by the treatment plan (collecting may include receiving/loading from an external source, retrieving from a memory, including a patient teeth datastore123or other memory, or the like).

The one or more processors102or any of the other elements (e.g., numeric function engine107, numeric function building engine109, comprehensive final position engine111, collision detector106, solution vector mapping engine113, etc.) may be connected in any appropriate manner and any of these elements may also be connected to the datastores (e.g., patient teeth datastore123, treatment targets datastore119, treatment details datastore117, treatment preferences datastore115, and numeric limits datastore121, etc.).

The numeric function building engine109may be used to select a plurality of numerically expressed treatment targets (e.g., from a treatment targets datastore119or other memory or input accessible to the one or more processors) based on the set of treatment details (which may be accessed from the treatment details datastore117or other accessible memory/input), the set of treatment preferences (which may be provided by the treatment preferences datastore115or other memory/input) and the comprehensive final position of the patient's teeth. The comprehensive final position of the patient's teeth may be provided by the comprehensive final position engine111or from a memory storing the comprehensive final position.

The solver may also include a numeric function minimizing engine107which may combine the plurality of numerically expressed treatment targets to form a single numerical function. This single numerical function may then be minimized to solve for one or more solution vectors using the collision detector106and a set of numeric limits that may be provided, for example, from a numeric limits datastore121or other memory/input. The numeric limits may be selected for the single numerical function based on the set treatment preferences (e.g., from the treatment preferences datastore115or other memory/input).

The solution vector typically includes all of the stages forming the treatment plan, and may be stored in a memory, and/or displayed, and/or transferred. In some variations the solution vector may be converted into a treatment plan using a solution vector mapping engine113to map the solution vector to a treatment plan, wherein the treatment plan includes a final tooth position that is different from the comprehensive final position of the patient's teeth.

FIG.2Cschematically illustrates a method of creating a treatment plan to align a patient's teeth using a plurality of removable aligners to be worn in sequential stages. In this example, the first step is to collect a digital model of a patient's teeth (e.g., upper or lower or both upper and lower arch)250. This may include, for example, receiving, in a processor, a digital model of a patient's teeth. The method may also include selecting a plurality of numerically expressed treatment targets (e.g., based on a selected set of treatment details, a set of treatment preferences, and a comprehensive final position of the teeth)252. The plurality of numerically expressed targets may then be combined into a single numerical function254, and a plurality of numeric limits on the single numeric function (e.g., based on a set of treatment preferences) may be selected256. The single numeric function may be minimized subject to the plurality of numeric limits to get a solution vector (including all stage form the treatment plan, use automatic collision detection)258. The process of solving (minimizing) for the solution vector may implement the collisions detection method (FIG.2D, described in greater detail below). The solution vector may then be mapped to a treatment plan260.

Method of Manufacturing a Series of Aligners

FIG.3is an overview of a method for manufacturing a series of aligners for a “partial treatment” plan. A partial treatment plan is a plan for which only a limited series of aligners is used to treat the patient; this limited number of aligners may be a predetermined number (e.g., 7, 10, 12, 16, 26, etc.) that is less than the total number that it may take to optimally correct the patient's malocclusions fully, addressing all of the clinically resolvable conditions (also referred to as treatment goals). In a partial treatment plan, the fixed number of aligners in the series may be configured (by configuring the treatment plan) to instead address some of the treatment goals within the limited number of stages defined, and approaching as closely as possible to the ideal realigned configuration without either creating new malocclusions or exacerbating existing malocclusions.

InFIG.3, the method starts by collecting from the patient (and by the user, e.g., dental professional), a model of the patient's teeth303, as well as any conditions (e.g., tooth movement restrictions) or preferences for treatment301; the method or apparatus may also optionally identify any general preferences that are specific to the dental processional302, and that may be applied to all of that dental professional's patients. In addition (and optionally) the method or apparatus may also provide an indication of the type of dental product (e.g., the type of dental/orthodontic products to be used to treat the patient304. All of this information, and particularly the prescription information, may be completed in a relatively short (e.g., 2-25, 2-20, 2-15, etc. lines) form or virtual survey. The user may submit this information to a treatment plan optimizing generator, which may be located at a remote site. The treatment plan optimizing generator, which is described in detail below, may use this information to generate a plurality of treatment plans. For example, the treatment plan optimizing generator may first prepare the model305, e.g., by digitizing it if it is not already a digital model, and by segmenting the digital model into individual teeth, gingiva, etc. Once prepared, the automated treatment planning307may be performed to automatically generate multiple treatment plans using, e.g., different numbers of stages; for each stage multiple variations including different treatment properties (e.g., IPR, attachments, etc.) may also be generated311. Each treatment plan is complete, and may be used to build an aligner series. For example, each treatment plan may include a new (and potentially unique) final position for the patient's teeth at the end of the treatment, staging showing the tooth movement and speed of movement for each stage (e.g., key frames) and a set of aligner features313. The corresponding aligner features may include the location of the attachments, etc.

This automated treatment planning may therefore use a treatment plan optimizing generator multiple times, each time providing slightly different treatment details and/or targets, while annotating each treatment plan with an indicator of what constraints and/or treatment targets were used to generate that treatment plan, including, for example, the fixed number of stages. The resulting multiple treatment plans may be collected into a single set (e.g., an array) and all of these treatment plans submitted back to the user via, e.g., a user interface to provide meaningful and interactive display, selection and/or manipulation of the treatment plans315. The user (e.g., dental professional) may then, using the interactive display, in real time, toggle between the multiple plans, and select one or a subset of treatment plans319. Optionally, the user may modify one or more plans319; if the user modifies a treatment plan in a manner that exceed the pre-calculated plurality of treatment plans321, then the modifications may be transmitted to back to the automated treatment planning subsystem (including the treatment plan optimizing generator) to generate additional treatment plans including the user's modifications337. These new treatment plans may replace or supplement the plans already pre-calculated.

Optionally, once a subset of treatment plans has been selected from the larger array of treatment plans, the user may present the subset of treatment plans to a subject323. The subject may be consulted to provide an indication (e.g., by showing the final stage/teeth position) of the orthodontic effect achievable by each treatment plan. Either the user or the subject (or both) may decide which treatment plan to choose, and the selected treatment plan may be forwarded on for fabrication/manufacturing325as discussed above.

FIG.4provides additional detail on one example of a consultation mode of operation of the system described herein. In this example, after the dental professional has selected two or more dental pans419(see alsoFIG.3,319), two or more of these dental plans may be presented to the patient433, allowing the patient to select between them. In addition to the image(s) of the teeth, including at least the last positon of the treatment plan, in some examples, metadata indicating the number of stages/length of treatment, and/or the treatment properties used to generate the particular treatment plan, etc., may be displayed as well. The display may be side-by-side435or it may be sequential, etc. The patient may then select between the presented plans435. Finally, and optionally, the user may finalize the treatment, and the selected treatment plan may be submitted for manufacturing437.

FIGS.5-6Bprovide more detailed examples of possible methods for manufacturing a sequence of aligners for a patient. InFIG.5, the user is presumed to be a doctor, through the user may be any dental professional. The user may first open a record for the patient, including any photos, using a user interface (IDS, a portal that the user may log into to access an account). A preliminary (automatic or manual) assessment may be performed to determine if the patient is a good candidate for the procedure (“case assessment”), and the user may review the case assessment. Thereafter, the user may submit a minimal patient prescription (e.g., indicating treatment goals, constraints, etc.). The user may further submit a model of the patient's teeth to the remote site for processing as mentioned above, to produce a digital model that is adequate for automatic treatment pan generation. In some cases a technician may perform digital “detailing” of the digital model to prepare it for processing. The treatment plan optimizing generator may then be used to automatically generate an array of alternative treatment plans (MTP) as discussed above. Thereafter, a user interface configured to allow interactive display of a plurality of different alternative treatment plans (“CCWeb”) may be used to review and select, and in some variations, modify, the treatment plans in the array of treatment plans. The patient may be consulted, as discussed above. Once the user selects a single treatment plan, and is satisfied with the treatment plan, the user may then transmit the selected treatment plan to the manufacturer (technician) who may (optionally) review and send a finalized version of the treatment plan for final approval. Once approved, the treatment plan, including all of the stages of aligners, may be fabricated using the treatment plan either directly or converting it into a manufacturing format. If the user is not satisfied with the treatment plan, it may be modified.

FIGS.6A-6Bshow a similar work flow to that shown inFIG.5. InFIGS.6A-6B, the user is presumed to provide the digital model of the patient's teeth at the start (e.g., by digitally scanning the patient's teeth).

FIGS.7A and7Billustrate examples of an interactive display of a plurality of treatment plans to allow a user to select between the treatment plans and/or modify the treatment plans as quickly and efficiently as possible. InFIG.7A, the display shows the final stage (final configuration) of each of the plurality of treatment plans. In this example, the plans are aligned side-by-side based on the number of stages (n1, n2, . . . nx). Each of these plans also includes optional variants (option1, option2, etc.) which may be displayed when the user control (box) is selected, which may be indicated by a check, as shown inFIG.7A.

FIG.7Bis similarly toFIG.7A, but lists each treatment plan as part of a ribbon that may be moved by sliding left or right, for example. Any of these user interfaces may show additional representations of the stages, either as key frames and/or as tooth representations.

FIG.7Cillustrates an example of a system. This system701is configured to provide interactive, real-time and dynamic comparison between different treatment plans. InFIG.7Cthe system701includes a plurality of modules that may operate together in any combination to provide real-time (or near real-time) interactive, dynamic display for comparison between multiple full orthodontic treatment plans, including rapidly toggling between different complete treatment plans to illustrate the differences between treatment plans having modified inputs (e.g., with/without IPR, extraction, etc.). For example, inFIG.7C, the system may include a user interface711for displaying (side-by-side and/or sequentially) different treatment plans. The treatment plans may be calculated as described herein, using a variety of different treatment preferences and/or treatment details. The treatment plans may be arranged in a grouping of any type (e.g., an array), and may be collected by the system (e.g., received, etc.) from a treatment plan generating system (such as shown inFIG.2A, above), and may be stored in a treatment plan datastore717for use by the system701. Each treatment plan of the plurality of treatment plans may include a set of sequential stages for orthodontic movement of the patient's teeth including a final stage. The final stage may represent the final position of the patient's teeth. In particular, these systems may be used when at least three of the treatment plans have different numbers of sequential stages, and further wherein the array of treatment plans comprises two or more treatment plans having different treatment properties. The different treatment properties may be stored for later use by the system in the treatment properties datastore715.

In operation the system may operate the user interface module711in conjunction with the user selectable controls705to allow the user to dynamically switch (toggle) between different treatment plans, which may be displayed on a screen or other display703of the system by showing one or more stages, including the last (final) stage (which may be represented by a digital model of the patient's teeth in this final position), and/or properties of the treatment plan, such as the number of steps/stages, the duration of treatment, the duration of stages, the rates of tooth movements, the movement of the teeth over time (e.g., by animation or still presentation), etc. The system may display images of the teeth at the final stage for each treatment plan of a subset of the treatment plans from the array of treatment plans on the screen. A treatment properties switch709module may provide real-time (or near real time) switching between images of the different treatment plans within the array of treatment plans, including switching between images of the various based on one or more user-selected controls on the screen.

The system may also include a communications module713(e.g., wireless module, such as Wi-Fi, Bluetooth, etc.). The communications module may allow the system to receive inputs and send outputs, such as, e.g., transmitting a selected one of the treatment plans for fabrication after the user has chosen the selected one of the treatment plans displayed on the screen.

Any of these systems may also be configured to allow the user to modify one or more of the treatment plans during the display, including modifying tooth position staging timing, etc. InFIG.7C, the system includes an optional Treatment plan modification engine713that may be configured to allow the user to modify a treatment plan directly.

FIG.7Dillustrates one example of a method of manufacturing a series of aligners for a patient's teeth. In particularly, this method may allow the real-time analysis and review of a huge number of treatment plans, selection of one of these treatment plans, and fabrication of a series or sequence of aligners based on these treatment plans. For example, the method may include: gathering (e.g., collecting, including collecting from a remote site) an array of treatment plans specific to the patient's teeth, wherein each treatment plan in the array describes a set of sequential stages for orthodontic movement of the patient's teeth including a final stage, further wherein at least three of the treatment plans have different numbers of sequential stages, and further wherein the array of treatment plans comprises two or more treatment plans having different treatment properties721. Images of the teeth after the final stage for each treatment plan of a subset of the treatment plans from the array of treatment plans may then be displayed on the screen723. The method may then switch, in real time, between images of the teeth at the final stages for different treatment plans within the array of treatment plans based on one or more user-selected controls on the screen725. Finally, a selected one of the treatment plans for fabrication that the user has chosen may be displayed on the screen and transmitted for fabrication. Once fabricated they may be sent to the patient or to the patient's dental/orthodontic provider for distribution to the patient.

FIG.8Ashows another example of a user interface that may be used to interactively review, modify and/or select a treatment plan. InFIG.8A, a patient record may be selected, and monitored using the interface. For example, the user interface may allow the user to interactively review the plurality of treatment plans generated; the user interface shown inFIG.8Ashows an example in which the patient's teeth model has already been submitted along with the user preferences, constrains, etc. and the treatment plan optimizing generator has already been used to generate an array including a plurality (e.g., 12 or more) of treatment plan variations.

FIG.8Bis another example of a user interface that may be used at the start of a patient treatment plan. InFIG.8B, the user interface is configured as an interactive prescription form that may allow the user (e.g., clinician, dentist, orthodontist, dental technician, etc.) to select the patient type (e.g., child, teen, adult), and enter information about the patient (e.g., name, age, images, etc.), and/or enter treatment/protocol preferences (e.g., eruption compensation, interproximal reduction preferences, attachment preferences, etc.). The user interface may also suggest one or more preferences from a library or database of preferences. In some variations the prescription form may also allow the user to manually enter treatment preferences. InFIG.8Bthe prescription form also allows the user to select the type of input of the patient dentition, such as from an intraoral scan and/or a scan of a mold or impression of a patient's teeth.

FIGS.9A-9B(similar toFIG.7A-7B) illustrate a user display that shows three (in this example) variations, side-by-side, of treatment plans for a patient (“Joe Smith”). As indicated on the right of the user interface, the patient has upper and lower crowding and an open bite (“malocclusion analysis”). The therapy may be configured to address these target goals. InFIG.9A, the three sets of treatment plans are shown, with user controls allowing selection of variations (that will swap with the variation treatment plan). On the left, a 26 stage treatment plan is shown; in the middle, a 14 stage treatment plan is shown; on the right, a 7 stage treatment plan is shown. For each treatment plan, variations include: with/without IPR, and with/without aligner attachments. By selecting the user control on the screen (or on an input such as a keypad, mouse, etc.), the user may see what effect adding/removing these features has. Further, any of these treatment plans may be selected and put into a subset for display to the subject as part of a consultation mode. Finally, below the image of the final stage position of the teeth for each variations is a textual description of the malocclusion analysis specific to that treatment plan. InFIG.8, all three basic parameters resolved the upper and lower crowding and both the 26 and 14 stage treatment plans addressed (and partially resolved) the open bite malocclusion.FIG.9Bshows the same basic user interface asFIG.9A, but with the 26 stage treatment plan shown as a variation including both IPR and aligner attachment.

FIG.9Cis an example of a user interface showing an interactive treatment planning screen in which a model (3D digital model) of the patient's dentition is included in a large display window. In some variations either or both the upper and lower arches are shown a selected stage (or stages) of a treatment plan, and permitting the user to select and apply various digital tools to modify the treatment plan (e.g., changing tooth number, adding/removing or moving attachments, adding/removing/modifying IPR between selected teeth, adding/removing pontics to selected teeth, etc.), manipulate the 3D model of the teeth (e.g., rotate, zoom, show just upper, just lower, both upper and lower, change the angle of display of the tooth to one or more predetermined angles, etc.), manipulate the display, including selecting a different stage of the treatment plan and/or show an image of the patient's smile as predicted for any stage (or just the final stage) of the treatment plan, showing a grip, and/or showing one or more analytics (e.g., Bolton ratio, bite analytics, etc.

InFIG.9Cthe user interface may also allow the user to both see and to modify the options applied in generating the treatment plan, including the name of the product (e.g., comprehensive, express, teen, etc.) having different properties for the proposed treatment plans. The properties (e.g., treatment duration/number of stages, minimal root movement, extractions, attachment restrictions, pre-restorative spacers, IPR, expansion (of dental arch) including which teeth to use for each, all, or some subset of these, elastic or surgical simulation, distalization, etc. The user interface ofFIG.9Cmay allow, as described above, any of the features of claims9A-9B, including selecting/deselecting one or more parameters.

FIGS.9D-9Fall illustrate alternative user interfaces as described herein. In general the term ‘user interface’ may refer to the interface seen by the user (doctor, dentist, dental technician, etc.), although, as described below, in some variations any of these user interfaces, or similar structures may be presented to the patient, including by the user, as part of the treatment selection and/or design process and/or during the treatment process. For example, inFIG.9Dthe user interface includes a window for showing one or both of the patient's dental arches at any stage of a proposed treatment plan (e.g., when a single treatment plan is selected or when only a single treatment plan is generated). The user interface may display the characteristics and/or user preferences that went into designing the treatment plan, such as the number or range of stages (e.g., a comprehensive plan having >21 stages), the amount of tooth movement (minimal or not), a description of the clinical goals (e.g., improving overbite, posterior cross bite, etc.), and aligner/staging features (e.g., pre-restorative spaces, IPR, expansion, proclination, extractions, elastic or surgical, distalization, attachments, etc.). The user interface may also provide 3D tools for manipulating the teeth and/or tools for modifying the treatment plan, and/or resubmitting for generating the new/revised treatment plan or series of plans. Finally, the user interface may allow the user to select/accept the treatment plan, so that the series of aligners may be transmitted for manufacture (e.g., which may include one or more additional quality control steps).

FIG.9Eis another example of a user interface, similar to that shown inFIG.9D, but including additional ‘tabs’ allowing the user to select between proposed treatment plans for direct comparison; the functionality of the user interface may be otherwise the same as described above. Each treatment plan may be separately or jointly examined. InFIG.9E, the user may toggle between treatment plans; in some variations, as described above, the user may be shown side-by-side windows allowing simultaneous comparison between two (or more) treatment plans, as illustrated inFIG.9F. In this example a pair of different treatment plans generated for the same patient are shown side-by-side; the user may select one or both to rotate (in some variations the user interface may be allowed to permit either separate rotation of the respective 3D models of the patient's teeth when showing stages of the treatment plan, or the user interface may be configures so that moving one of the 3D models of the patient's teeth in a particular treatment plan may automatically move the other 3D model of the patient's teeth according to the second treatment plan.

In some variations the user interface may be configured to display a modified image of the patient's smile (e.g., the patient's teeth in a forward-facing image of the patient's face) at the conclusion of (or at any stage of) a treatment plan.FIG.9Gshows an image of an initial malocclusion (left image) for direct side-by-side comparison with a simulated image of the patient's smile following a particular treatment plan (right image); the specifics of the treatment plan are listed on the user interface (right side). In this example, the user may toggle between different treatment plans by toggling (in the controls on the right) various features on or off, such as overbite correction, posterior crossbite correction, molar class correction, overjet correction, IPR, attachment positions, number of stages (e.g., product), etc.

As mentioned, in some variations a specific output (including a specific user interace) for presenting one or more treatment plans to a patient may be used.FIG.9His an example of a patient presentation user interface that may be provided to the patient to illustrate the predicted outcome of the treatment, and/or to allow a comparison between different treatment plans. The user interface inFIG.9His a simplified version of the user interfaces discussed above, showing images of the smile (face) with a simulated patient tooth position, and/or images of the patient's teeth. The images may be manipulated by one or more controls (e.g., shown on the top of the user interface inFIG.9H, including zoom, rotate, arch views/angles, etc.). InFIG.9H, “smile” view is selected and the final tooth arrangement for each of two treatment plans is shown.

FIGS.10A-10Cillustrate a user display screen including controls for displaying one treatment plan in detail, and/or for modifying the treatment plan. InFIG.10Aa treatment plan having 26 stages is shown. A display of the teeth at each stage is shown in the middle of the screen and this display may be changed by moving the slider (control1005). One or more controls may also be used to change the view of the teeth shown1007. Patient information may be shown1009, as well as product information1011. Treatment details and/or treatment preferences corresponding to the treatment plan being displayed may also be shown1013. InFIG.10A, the display indicates that the treatment plan was created allowing both interproximal reduction (IPR) and attachments. The exemplary display shown inFIG.10Aalso indicates that this treatment plan resolves treatment concerns1015; specifically this treatment plan resolves both upper and lower crowding and open bite. In addition, the display also includes a control allowing this treatment plan to be added to a subset of plans for consultation and/or for selecting this plan to order1019. A display such as the one shown inFIG.10Amay be selected from any other display of the treatment plans, such as shown inFIGS.7A-9B.

FIG.10Bshows the display ofFIG.10Ain which the treatment plan is being modified by the user. In this example the treatment plan is being modified to adjust interproximal spacing1021, shown by the + symbols on the teeth. In addition, the amount of leveling may also be adjusted. Additional modifications, and tools to control them, may also be included. Other controls on the screen may allow the user to communicate directly with a technician1025, or to order a series of aligners based on this treatment plan1027, and/or to enter into the consultation mode1031. For example, selection of the control to order the plan may result in a confirmation screen, such as shown inFIG.10C.

FIG.11Ashows the exemplary screen ofFIG.10A, configured for communication with the technician, as mentioned above. In this example, the user may add instructions or preferences to annotate the treatment plan for modification. These text notes/instructions may be typed in by the user, or they may be selected from a menu of notes. InFIG.11A, the instructions/notes1105include treatment preferences stating: “do not move upper and lower 3rdmolars” and “do not retract upper teeth.” Additional comments may allow the user to submit1107or discard1109the comments. When the treatment preferences are submitted, the apparatus may indicate a confirmation screen1111as shown inFIG.11B.

As mentioned above, the methods and apparatuses (e.g., software, firmware, hardware or some combination of these) may be configured to include a consultation mode.FIG.12illustrates one example of a consultation summary screen. This screen may be used by the user before entering into a consultation mode, or it may be used as part of the consultation mode. In general, the consultation mode may display a subset of the array of treatment plans; the treatment plans included in the subset may be selected by the user, or in some variations may be automatically selected based, e.g., on known user preferences. These selected treatment plans may then be presented, using the consultation mode, to the subject. InFIG.12, the consultation summary screen shows two treatment plans1201,1203as both images of the teeth (at the selected stage of treatment to be shown) and treatment details or treatment preferences1215(e.g., allowing/not allowing IPR, allowing/not allowing attachments, etc.). The display may also show the treatment concerns that are addressed by each treatment plan1217(e.g., resolved upper and lower crowding, resolved open bite, etc.). This may allow direct, including side-by-side, comparison by the patient. The screen inFIG.12also illustrates the patient information, including name1220(“Joe Smith”), the initial positions of the teeth1221, an image of the patient1223, and an analysis of the initial malocclusion(s)1225. Controls on the display may allow the user to enter a consolation mode, in which a simplified display of the treatment plans may corresponding to various treatments may be shown to the patient.

FIG.13, shows a “consultation mode” display screen, for display to a patient based on the subset of treatment plans selected by the user. InFIG.13, the consultation mode screen shows two selected treatment plans1303,1305, for comparison with the patient's current dentition1301. The first treatment plan is a 26 stage plan1303, while the second treatment plan is a 14 stage treatment plan in this example. Any subset of treatment plans may be shown. In this example, the various treatment plans are shown with annotation indicating how well they address the patient's identified malocclusions1307. For example, the 26 stage treatment plan (which may correspond to a first product) resolves both the upper and lower crowding and the open bite1309. The 14 stage treatment plan (which may correspond to a second product) resolves the upper and lower crowding, and partially resolves the open bite1312.

From the consultation mode, the user and/or the patient may review, in a sequential or side-by-side display, the various selected treatment plans, and may select between them. The consultation mode may also include information about the cost and/or timing of the treatment plans (including the number of stages, etc.).

FIG.14is an example of a display for showing detail (including animation) for a particular treatment plan. Individual stages may be selected.

In general, patient information, including dental record information, may be shown as well. For example, as a reference, the methods and apparatuses may include a display of the patient's upper and lower arches (e.g., seeFIG.15). InFIG.15, the display shows images of the upper and lower jaw at two times (e.g.,2005and2011) for the patient. This type of display shows the progression of the malocclusion over time. InFIG.15, the malocclusion includes a slipped contact and mesial drift.

As mentioned above, the array of treatment plans may typically include three or more (more preferably 12 or greater) treatment plans.FIGS.16A-16Millustrate one example of an array of treatment plans for a patient.FIG.12Ashows an example of the patient's actual dentition, shown as a digital model. As discussed above, this model may be generated from a direct digital scan of the patient's teeth, or from an impression.FIGS.16B-16Millustrate12alternative treatment plans generated for the patient and combined into an array of treatment plans that the user may select from or modify further.FIGS.16B-16Mare arranged as a grid, for convenience, and a model of the final tooth positions, following completion of the treatment plans, is shown. The actual treatment plan may include an indicator of position and/or orientation of each tooth, as well as key frames describing how to translate from the initial position (e.g.,FIG.16A) to a final position (FIGS.16B-16M). InFIGS.16B-16D, shown as the horizontal axis, each of the three treatment plans is shown having been calculated with the treatment details or treatment preferences set to not allow attachments and not allow IPR. The figures also show the use of 26, 15 or 7 stages, respectively forFIGS.16B-16D.FIGS.16E-16Gshow a series of treatment plans (again 26, 15 or 7 stages, respectively) for which the attachments were allowed, but not IPR.FIGS.16H,16I, and16J(26, 15 or 7 stages, respectively), show examples of the final stages of treatment plans in which attachments were not allowed, but IPR was allowed. Finally,FIGS.16K,16L, and16M(26, 15 or 7 stages, respectively), show examples in which the treatment plans were generated allowing both attachments and IPR.

An alternative treatment plan display and modification screen is shown inFIG.17. In this example, the treatment plan is a 26 stage plan. The initial display is the 26 stage device which did not allow either IPR or attachments. InFIG.17, the right half of the screen shows controls, configured as filters that may be selected to toggle between the different treatment plans. Because the treatment plans are all pre-calculated and included it the array of treatment plans, they may be easily and quickly toggled between each other, even in very large or complex treatment plans.FIG.17shows controls that allow the display to switch between a treatment plan allowing IPR/not allowing IPR1703, and treatment plans that allow or do not allow attachments1705. Additional other controls may allow the user to toggle between different products having different treatment durations (stages)1707. InFIG.17, the apparatus may also allow the user to select different treatment details1709.

Treatment Plan Optimizing Generator

Also described herein are the methods and apparatuses for automatically creating a treatment plan to align a patient's teeth using a plurality of removable aligners to be worn in sequential stages. These methods and apparatuses may include creating a plurality of variations of treatment plans to align a patient's teeth using a plurality of removable aligners to be worn in sequential stages. The method may be referred to herein as a method for automatically generating optimized treatment plans, and the apparatus (e.g., software, including non-transient, computer-readable medium containing program instructions for creating a treatment plan to align a patient's teeth using a plurality of removable aligners) may be referred to as a treatment plan optimizing generator.

The methods for automatically generating optimized treatment plans described herein may simultaneously optimize final position and intermediate teeth positions (e.g., staging). This may allow the apparatus to produce treatment plans having a final position that is achievable in exactly the allowed number of stages (and therefore duration of treatment) for a product corresponding to a set number (or range) of aligners.

The comprehensive treatment plans built using the methods of automatically generating optimized treatment plans described herein also incorporate an optimized or idealized treatment plan (which is referred to herein as a comprehensive treatment plan) generated without consideration of the amount of time or number of stages it may take to achieve. This may enable the method to improve orthodontic measurements that are not explicitly defined as optimization goals. Measurements that represent potential orthodontic problems may be restricted to a range between the initial positions (or values) of the patient's teeth and the positions (or values) planned in the comprehensive treatment. This ensures that partial final position does not introduce or worsen orthodontic problems unnecessarily.

As an alternative to the methods and apparatuses described herein, a treatment plan may be created by first building (manually or automatically or a combination of manually and automatically) the comprehensive treatment plan, and then segmenting the plan into a series of movement-limited stages. In this method, the number of stages depends upon the final positions of the teeth. Stages are determined by, e.g., iteratively simplifying the leading tooth movements.FIG.18shows one example of a process flow for this method, in which the initial position of the teeth is provided along with the user (e.g., dental professional's) prescription and preferences as inputs to generate the final potion of the teeth (e.g., the comprehensive treatment plan). The final position produced by this method may not always satisfy product constraints due to inaccuracy of treatment length estimation. Further, straight-forward simplification of tooth movements that may be required to segment the steps of the plan may unnecessarily compromises quality of the final position. Finally, treatment plan may not prioritize aesthetic goals over orthodontic norms and rules, achieving sub-optimal resolution of the likely patient's chief concerns. Although these problems may be mitigated by personal judgement of technicians, such manual adjustments may take significant time and the produced plans may lack consistent quality.

The method inFIG.18, which involves sequentially solving for a comprehensive final position (“final position generation”), then segmenting this into a series of aligners (“staging generation”) and finally outputting the treatment plan including both the final position and staging (“output”) is a linear process, although it may include iteration to adjust the final position and/or staging. As mentioned above, there are often situation in which it is desirable to pan a treatment in which the parameters such as the length of treatment are constrained. Further, it would be beneficial to provide methods and apparatuses for treatment planning in which the entire treatment plan (e.g., each stage) is determined at the same time, rather than sequentially.

Described herein are methods and apparatuses for generating orthodontic treatment plans by expressing the target treatment goals for tooth movement as numerical expressions and limiting these target treatment goals by numeric constraints corresponding to limits on the treatment. Once the treatment goals and limitations are defined numerically, the resulting numeric expression (e.g., equations) may be treated as a non-linear optimization problem and solved to generate an optimal treatment plan given the constraints and target goals. These method may result in generating treatment plans that may be referred to as “partial plans” because they are not intended to fully resolve all of the patient's clinical orthodontic conditions, but may best resolve them within the given product limits (e.g., within a limited treatment time/number of stages, etc.).

FIG.19schematically illustrates a simplified overview of the concept underlying the method for automatically generating optimized treatment plans described herein. InFIG.19, the region within the circle1903represents all of the treatment plans and final positions that may be achieved from a patient's starting tooth configuration (shown as the central circle1905, in the upper left). The circle therefore contains all of the final tooth positions and treatment plans for achieving these final positions when the treatment plan is constrained by the limits of the aligner system (e.g., the limits on the number of stages, the limits on the amount and rate of movement of each tooth, etc.) and the limits required by the dental professional (e.g., restricting movement of some teeth, etc.). These limits may be referred to as the treatment preferences and the treatment details. The circle shown inFIG.19is highly simplified; the space bounded by the constraints may be multi-dimensional, but the principle concept is the same as shown inFIG.19.

A comprehensive treatment plan is typically determined without concern for all or most of the constraints forming the boundary1903. Thus, inFIG.19, the comprehensive treatment plan (“ideal final”)1907is shown located outside of the space formed by the boundary1903, although in theory it may be inside or outside. An image of the final tooth position corresponding to the comprehensive treatment plan is shown in the bottom right ofFIG.19. Since this orthodontically ideal final position may not be achievable within the boundary, the space contained within the boundary must be examined to identify the next-best treatment plan that satisfies as many of the treatment concerns while providing an aesthetically pleasing result.

One possible solution may be to find the treatment plan within the boundary that is close to the ideal final position. InFIG.19, the closest position1909results in a final position of the teeth that is unsatisfactory. As shown in the upper right corner ofFIG.19, the treatment plan that is closest to the ideal final position within the boundary is does not resolve the principle concern (e.g., crowding) though it may address other concerns (e.g., leveling, etc.), and instead creates or makes worse other problems, such as spacing of the teeth. Although almost all of the teeth, except one, achieved a final position nearly identical to the ideal final position, the resulting final position is both orthodontically and aesthetically unsatisfactory.

Instead, the optimal position1911that both resolves the principle concern (e.g., crowding of the teeth) and results in an aesthetically pleasing result is shown in the bottom left ofFIG.19. Although fewer teeth achieved the final position that is the same as the optimal position, the resulting final position is superior to the closest position shown.

In practice, the ideal fit may be found by expressing the constraints as a numeric expressions and a set of limits on these numeric expression and solving the resulting expression as an optimization problem. Specifically, the method may include identifying, for a particular patient, a set of treatment preferences and treatment details, expressing these treatment preferences and treatment constrains as a nonlinear expression, and solving the optimization problem.FIG.20Aillustrate a schematic of this method. InFIG.20A, the input into the method (or an apparatus performing the method) is the initial position of the patient's teeth, the dental professional's prescription and preferences, and the definition of the product. The definition of the product may be thought of as the set of treatment preferences. This may include, for example, the number of stages, the properties of the aligners including the rate of movement of the teeth by the aligner, etc. The user's prescription and preferences may correspond to the treatment details.

In any of the methods and apparatuses described herein, it may be beneficial to have an ideal tooth position (e.g., the comprehensive final tooth position) for use in the treatment planning. However, it should be clear that this comprehensive final tooth position is not used as the actual final tooth position. Instead, the methods described herein concurrently determine both the actual final tooth position and the stages required to achieve that tooth position within the limits required by the treatment preferences and treatment details. Software for determining a comprehensive final position may be used (which may also be referred to as “FiPos” software) or the final position may be manually, or semi-manually/semi-automatically determined either digitally or manually (e.g., using a model of the patient's teeth) and digitized.

Once a comprehensive final tooth position has been identified (“Full Final Position Generation”), this final position may be used, along with the initial position, treatment preferences and treatment details, to determine the optimal treatment plan, using “optimization treatment planning.” This optimized treatment planning is described in greater detail below. The optimization treatment planning may include result in a vector description including the staging, key frames (showing movement of the teeth between stages) and a proposed final position of the teeth, which may be output (“output”) by the system.

FIG.20Billustrates this method is slightly more detail, showing the rules and problems to be solved for the determination of the comprehensive final position, as well as an example of the rules and limitations for determining an optimization problem that can be solved for an optimized treatment plan.

InFIG.20C, the same four inputs (product definition/treatment details2003, preferences (treatment preferences, user-specific and/or patient specific)2005, initial tooth position2007, and comprehensive tooth position2009) are used by the treatment plan optimizing generator to select a plurality of numerically expressed treatment targets from a memory accessible to the processor2011. The memory may generally include a set of pre-defined generic expression (“merit functions” or merit function components, or “target functions”) that describe the numerically expressed treatment targets. Typically each of these targets is a numeric function that has a value that is closest to zero for ideal cases. For example, as will be described below, if the treatment target is alignment in an x direction, the numeric function may express the deviation from alignment in the x direction as a numeric vale (e.g., from 0, meaning in alignment, to some distance, e.g., in mm, out of alignment).

Similarly, the treatment preferences may be expressed as limits on the target functions. The treatment preferences, and in some variations treatment details, initial positions and comprehensive positions may be used to select the numeric limits from a stored set of pre-defined generic constraints. Once the numeric limits and target functions have been selected (e.g., based on the set of treatment details, the set of treatment preferences and the comprehensive final position of the patient's teeth)2015, resulting in the specialized constraints (limits)2017and specialized numerically expressed treatment targets (target functions)2019, they may be expressed as a non-linear optimization problem2021by first combining the plurality of numerically expressed treatment targets (target functions) to form a single numerical function (single numerical merit function). Each numerically expressed treatment target may be multiplied by a scaling factor. The resulting non-linear optimization problem is a single numerical function subject to the plurality of numeric limits2023.

Thereafter, the optimization problem may be solved using conventional techniques, such as an interior point method. Such nonlinear constrained optimization solution techniques2025may minimize the single numerical function subject to the plurality of numeric limits to get a solution vector including all stages forming the treatment plan2027. The solution vector may be mapped to a treatment plan2029, wherein this “optimized” treatment plan2033includes a final tooth position that is different from the comprehensive final position of the patient's teeth.

An optimized treatment plan may be identified by solving an optimization problem once the constraints on the patient's teeth (e.g., product definition/treatment details and treatment preferences) are expressed as numeric functions and limits. Non-linear constrained optimization problems can be represented by a merit function and a set of inequality constraints:

minimizef0(x)subject⁢tofi(x)≤0,i=1,...,m,xjmin≤xj≤xjmax,j=1,...,n.

See, e.g.,FIG.21. To produce treatment plan by solving optimization problem, the treatment plan is described in terms of distinct values, which are mapped to xjvariables in the problem statement. One possible mapping, used in the first implementation of the method, is described below. The position of each tooth at the final stage is described in terms of six coordinates (orientation, e.g., rotation, and translation from the center of the jaw) and mapped to six variables. Staging, i.e. intermediate positions, of each tooth is described as a linear combination of several functional component. Each component describes deviation from linear movement at a certain stage and is parametrized by six coordinate deviations and a stage number. Thus, each functional component is mapped to seven variables in optimization space, per tooth.

The numeric limits on the single numerical function are understood to be qualities of treatment plan that must never be violated and may be defined as inequality constraints Constraints enforce mechanical, biomechanical, clinical and aesthetic rules, as well limits imposed by product definitions. Implemented constraints include, but are not limited to, amount of reproximation, maximum velocity of tooth movement, depth of inter-arch collisions, cusp-to-groove occlusion. Example of constrains also include “do-no-harm” constrains that ensure tha the movement of the teeth does not result in making the alignment worse or overcorrecting, e.g.: midline, overjet, overbite, occlusion, misalignment, spaces, rotations, etc. Other constraints may include: amount of collisions, movement velocities and separation of movements, etc.

Qualities of treatment plan that must be improved as much as possible within constraints are defined as numerically expressed treatment targets, i.e. components of merit function, ƒ0. Targets are typically features that are to be improved or modified by the treatment. Targets may include, but are not limited to, length of the resulting treatment, amount of spaces, misalignment between teeth, etc. For example, potential chief concerns may include: misalignment (x and z), de-rotation, occlusion, diastema and spaces, inter-arch collisions, etc. Other targets may include: closeness to comprehensive setup, and roundtrips. The merit function(s) are defined as a non-linear combination of target functions, weighted by pre-defined coefficients. All of the target functions may be summed (and weighted) to form a single numerical function (single numerical merit function).

For example, target functions that may be weighted, summed and minimized as described herein may include: minimal difference with ideal final position (with the target of trying to achieve an ideal final position); misalignment, e.g., by minimizing the difference between x- and z-misalignment in value final position and in ideal one; tooth to aligned to arch (e.g., minimize the angle between the x axis in a value final position and an ideal one); minimal diastema (e.g., minimize spaces between neighboring teeth); occlusion (e.g., applicable for cases with both jaws, pull corresponding cusps from one jaw to the groves from opposite jaw); round-trip (e.g., minimize mesial-distal and buccal lingual round-trips); inter-arch collisions in value position (applicable only for cases with both jaws, e.g., try to create inter-arch collision at posterior teeth as close to ideal final position as possible); inter-arch collisions during staging, etc.

In general, measurement may be a function implemented in software that can be used as target or constraint in the optimization problem. The input for every measurement may be: 3D models of all teeth (constants), six coordinates per tooth that define the tooth position relative to the jaw. The output of every measurement may be a single numerical value, such as distance in mm, angle in radians, or score from 0 to 5.

Examples of targets are shown inFIGS.22A-25illustrate examples of targets and constrains that are expressed as numeric functions and limits. For example,FIG.22Ashows one method of quantifying occlusion (e.g., between upper and lower jaws). InFIG.22A, the occlusion metric is the cumulative distance between all corresponding cusp points from one jaw and groove spline from opposite jaw. For the upper jaw, lingual cusps are used and for the lower jaw, buccal cusps are used. Thus, the quality of the occlusion is measured as a function of distances between occluding grooves and cusps. The constraints of the optimization problem may ensure that quality of occlusion in partial setup is not worse than the patient's initial position. As a result, if the patient's cross bite cannot be fully fixed with good occlusion in low-stage product, it will not be corrected. This is illustrated inFIGS.22B-22D.FIG.22Bshows a view of a patient's initial tooth configuration (cross bite).FIG.22Cshows the correction using a comprehensive final position to correct.FIG.22Dshows a comparable correction using a ‘partial’ optimization setup as described herein.

FIG.23shows an example of the quantification of x-misalignment. X-misalignment is a projection of a line between buccal ridge end points of two neighbor teeth onto the arch normal in a given stage2303(yellow line). Similarly,FIG.24illustrates quantification of z-misalignment. Z-Misalignment is a projection of a difference of tooth tip point onto the jaw occlusal plane's normal in a given stage2403.

FIG.25illustrates alignment to arch quantification. As illustrated, alignment to arch for a given tooth is the angle between a projection of X axis in a value final position and an ideal one.

Examples of constraints include tooth movement limits that typically require that the range of movements that are allowed are limited for every dental type according the product definition. These limits may be defined clinically to ensure that the proposed treatment plans are achievable in practice with the device to be used. Each product (e.g., aligner) may different set of values, which may be stored in a look-up table or other memory accessible by the processor.

Tooth movement limits may include rotation (e.g., tooth rotation along z axis); tip (e.g., tooth rotation along x axis), torque (e.g., tooth rotation along y axis); crown movement, including horizontal crown movement (e.g., translation along z axis ignored), buccal-lingual crown movement (crown center translation along x axis), mesial-distal crown movement (e.g., crown center translation along y axis); mesial-distal root apex movement (e.g., root apex translation along y axis); buccal-lingual root apex movement (e.g., root apex translation along x axis); extrusion/intrusion (e.g., tooth translation along z axis); and relative extrusion.

Collision constraints may also be used to limit collisions between teeth. Further, staging constraints may be applied to intermediate stages (e.g., key frames) to ensure that the treatment is plan is consistent and clinically predictable. Collision constraints may include inter arch collision (applicable only for cases with both jaws), which forbids deep collisions greater than, e.g., 0.05 mm in depth, on the posterior teeth and may forbid smaller or equal depth in anterior teeth in the value final position. Collision constrains may also forbid one arch collision (e.g., so that collision between neighbor teeth in value final position does not exceed a maximum of collisions in initial, ideal final or value corresponding to the tight contact).

Staging constraints may also be used. For example, stating constraints may include synchronized finish of value final positions (e.g., every tooth must complete movement at the same stage number); fixed stage constraints (e.g., every tooth starts movement at stage 0); “not greater stage” (e.g., the final stage number, treatment length, must not be greater than allowed in the product (i.e. 20 stages, etc.); a “do not trigger Stairs pattern” (e.g., do not exceed mesial-distal movements on every tooth that can be predictably achieved in practice without long sequential teeth movements, referred to as a stairs pattern); constraints so that no Z-rotation and Intrusion/Extrusion round-trips occur on any tooth; and velocity rules (e.g., tooth movement over a single stage, e.g., aligner, must not exceed 0.25 mm).

Other examples of constraints include “do no harm” constraints, which ensure that planned final position does not introduce or worsen orthodontic problems. In the optimized final position, the value of every measurement that corresponds to an orthodontic condition must lie within the value measured in initial position, and the value measured in the comprehensive (ideal) final position. For example, overjet may be limited (applicable only for cases with both jaws) by requiring that each jaw should have at least one incisor for each side. Overbite may be limited (applicable only for cases with both jaws); each jaw should have at least one incisor for each side. Midline may be limited (applicable only for cases with both jaws); each jaw should have more than two anteriors. Occlusion may be limited (applicable only for cases with both jaws). X- and z-misalignment may be limited (applicable for each pair of neighbor teeth where at least one tooth is movable); arch and jaw occlusal plane may be calculated once in initial position. Spacing (applicable for each pair of neighbor teeth where at least one tooth is movable) may be limited; crown space between neighbor teeth should not exceed maximum of spaces in initial and ideal final positions. Angular may be limited by keeping teeth axes between initial and ideal final position (alignment to arch measurement for x, y and z axes).

Once the problem is stated in this manner it can be solved by any constrained optimization algorithm of sufficient power, such as an Interior Point method. The result is a solution vector. The vector will include position and orientation values for each tooth, as well as stage number corresponding to each tooth. The vector may describe a large number of such values, e.g., xjvariables.

The produced solution vector of optimal values of xjvariables may be converted to the treatment plan by the mapping of variables described above in reference toFIG.20C.

In general, these methods may be used to generate partial treatment plans that are characterized by addressing patient's concerns as much as possible within the product limits. In contrast to comprehensive, or full, treatment plans that have as their end point the ideal, comprehensive tooth position, these partial treatment plans may not fully resolve all of the concerns of the dental professional, and may not address all orthodontic problems. To produce such partial plan, treatment length and tooth limits allowed within the product are implemented as inequality constraints. This forces the optimization algorithm to find a solution, i.e. treatment plan, within the product limits, that improves merit function as much as possible, but not to the full degree.

In general, to improve quality of the plans, an optimization target (e.g., the comprehensive tooth position) may be added to minimize distance between the partial plan and the comprehensive treatment. This distance can be measured by a length of secondary treatment that achieves comprehensive final position starting from the partial final position. Full final position for the comprehensive treatment plan may be produced manually, automatically or semi-automatically, as mentioned above, and is stored separately in apparatus. Once the partial treatment plan is ready, full final position is discarded.

To ensure that the partial treatment plans generated as described herein (optimized treatment plans) do not introduce or worsen orthodontic problems, additional inequality constraints may be introduced. As discussed above, each identified orthodontic problem, such as deep bite or class, may be measured as a single numerical value. Next, two inequalities constrain such measurement in partial setup to the range between the initial value and the comprehensive treatment. Former inequality ensures that partial setup does not worsen the problem over the initial position. The second (optional) inequality may ensure that partial setup does not overcorrect the problem unnecessarily.

By including a comprehensive final position, and incorporating it the merit function and constraints of the non-linear optimization problem, and solving this problem using the generic optimization algorithms, the method described herein may produce treatment plans that fully satisfy the constrains from the product and user preferences, while optimally resolving chief concerns, improving and maintain other orthodontic measurements.

The methods described herein can be straight-forwardly applied to all products with limits on number of stages or amount of tooth movement. By building such plans automatically, they may enable a dental professional to review multiple plans for a product range, or customize product while reviewing the updated treatment plan, as described above. Restriction on the number of stages may be replaced or supplemented with other restrictions and goals; this may allow the method to incorporate chief concerns, doctor's preferences and predictability models into comprehensive treatment plans as well.

The methods and apparatuses described herein are also fully compatible with the use of biomechanical solutions that can potentially be combined with optimization of final and intermediate tooth positions to produce treatment plans with movements that are fully supported by the appliance (e.g., aligner) design.

Collision Detection

Construction of orthodontic treatment for a patient must account for limitations on mutual position of teeth, including amount of space and interproximal reduction. Computing exact amount of collisions and spaces between teeth may be a computationally intensive operation that impacts cost and quality of automatic treatment plans. Described herein are methods and apparatuses (e.g., such as system for automatically detecting collisions between teeth, which may be referred to as collision detectors) for constructing approximated shapes of teeth by packing the surface(s) of the teeth, or in some variations, other structures (e.g., attachments, brackets, etc.) using multiple three dimensional (3D) shapes (such as capsules) having a planar figure (e.g., line, rectangle, etc.) in the core, and an outer surface extending a constant radius from the core in x, y and z. Collisions (e.g., overlap) between the teeth may be analytically determined from the 3D shapes with high precision. These systems and methods may also be applied to just adjacent portion of the teeth (rather than the entire teeth) and may be combined with a hierarchy of bounding boxes in order to accelerate the computation. Compared to precise generic technique or estimating collision, these methods and apparatuses described herein may be two or more orders of magnitude faster, and may allow the systems and methods described above for calculating one or more treatment plans (e.g., a solver or a treatment plan solver) to incorporate these collision detectors. Furthermore, any of the methods and apparatuses described herein may determine both the magnitude of the overlap (or in some cases, the closest separation) between the teeth, but may also be configured to determine the velocity of the overlap (e.g., in three or more spatial directions, such as x, y, z and/or yaw, pitch, roll).

FIG.29Aillustrates the use of a triangular mesh2905to model the surface of a shape, such as a tooth. Surface modeling using a triangular mesh may be used to model adjacent teeth and the modeled surface may be used to estimate the distance between objects such as teeth.FIG.29Bshows an example of a group of three-dimensional (3D) shapes, shown as capsules, in which the 3D shapes each have a core that is a line or a plane figure and an outer surface that is a constant radius from the core. InFIG.29Bthe capsules2907are formed by a core that is a line. As will be described in greater detail below, modeling the surfaces of adjacent teeth by packing these surfaces (and internal regions) with capsules as described herein may be used to determine collisions between the shapes much more rapidly than other methods, including modeling by triangular mesh, as shown inFIG.29A. For example, a tooth surface may be modeled with high precision using 2000-8000 triangles; the same surface may be modeled using 50-200 capsules with nearly equivalent precision. Because the capsules have both flat and convex regions they may be particularly well suited to modeling shapes such as the surface of a tooth. Using 3D shapes having a constant radius from a planar shape (e.g., line, rectangle, etc.) may be used to calculate the distance between the surfaces more than five times faster compared to modeling with triangles at an equivalent precision. The 3D shapes, such as capsules, are typically solids, and may therefore be used for fast penetration depth computation.

FIG.29Cshows a side-by-side comparison of a tooth modeled with both capsules2917(entire tooth) and triangular mesh (right side2915). In practice, the patient's teeth only need to be modeled by packing with three dimensional shapes such as capsules once; thereafter the overall tooth position may be changed, but the same surface modeled by the 3D shapes may be used to examine collisions/spacing for multiple different arrangements of the teeth.

Any appropriate 3D shape having a core that and an outer surface that is a constant radius from the core may be used, although it has been found that using shapes with at least partially linear cores (e.g., capsules, rounded rectangles, etc.) may be particularly beneficial for modeling the tooth surfaces and estimating distanced, including collisions, and depths of collision. For example,FIGS.30A-30Cshow sections through 3D shapes having a core and an outer surface that is a constant radius from the core are shown; the corresponding figures shown are shown in perspective view inFIGS.31A-31C. InFIGS.30A and31Athe shape is a sphere having a core3001that is a point at which the radius, r,3003originates. The use of a sphere, which has only a concave outer surface, for packing a complex shape such as the tooth surface may be suboptimal, in part because the surface of the tooth includes regions that are not concave. The use of spheres may require a larger number of smaller spheres for packing to approximate the tooth surface compared to other shapes such as capsules like those shown inFIGS.30B and31B. InFIGS.30B and31B, the capsule has core that is a line segment3005, and an outer surface that is a constant radius, r,3007on all side of the line in x, y and z space. Similarly,FIGS.30C and31Cshow an example in which the core is a closed planer shape, shown as a rectangle3009having a constant-length radius3011extending from the surface. The outer surfaces are shown in the perspective views ofFIGS.31A-31C.

When modeling the tooth using the 3D shapes such as capsules, a variety of different capsule sizes may be used; the capsules may have different lengths of the core line segment, and/or the radius of each capsule extending from the core may be different (though typically the same radius length in an individual capsule). Alternative or additionally, different 3D shapes may be used.

FIGS.32A and32Billustrate top and side perspective views, respectively, of a patient's molar3201that has been modeled using a plurality of capsules. In this example, the entire outer surface of the portion of the tooth above the gingiva has been modeled by packing with capsules. In practice one or more teeth may be modeled from a digital model of the patient's tooth or teeth. For example, a digital scan of the patient's teeth (e.g., from an intraoral scan, a scan of an impression of the teeth, etc.) may be provided and the surface of the teeth may be modeled by packing the tooth surface (and all or the peripheral region of the tooth volume) with a plurality of 3D shapes, such as capsules. An optimization algorithm may be used to automatically position a small number of capsules to approximate the tooth surface as close as possible. The precision of the match with the tooth surface may be set as a parameter, so that the minimum number of capsules (or maximum size of capsules) necessary to model the surface within the set precision may be determined.

In variations in which the patient's teeth are digitally scanned, the digital scan may be segmented into individual teeth (or groups of teeth) and each segmented region, e.g., tooth, may be modeled with 3D shapes (e.g., capsules). In some variations the tooth or teeth may already be modeled in another manner (e.g., by triangles as described inFIG.29A) and the existing model may be modeled with the 3D shapes.

To model an individual tooth (or group of teeth), the tooth may be packed with capsules so that difference between tooth's surface and the outer surface of the capsules is as low as possible. In this model, only the 3D shapes, e.g., capsules, are used for approximations; these 3D shapes may be constructed quickly and may be analyzed quickly. As will be described in greater detail below, in some variations, only a part of a tooth may be approximated. For example, only the IP area, incisal area, crown, etc. may be modeled; for example, only the side of the tooth facing the adjacent tooth may be modeled. Alternatively, the whole tooth shape may be modeled. In some variations, the tooth shape may be decimated before approximating. For example, the tooth shape may be simplified by filtering (e.g., smoothing, etc.). Alternatively or additionally, the original shape can be used to obtain more precise approximations. In some variations, all of the teeth (or subsets of teeth) can be modeled simultaneously, e.g., in parallel. Alternatively, teeth may be modeled one-by-one, e.g., sequentially.

Modeling the tooth may be iterative. The surface may initially be filled with non-overlapping 3D shapes (e.g., capsules) as a starting configuration. Each iteration may include: finding the area of shape which is approximated by capsules the worst (e.g., comparing the digital tooth surface, or “actual surface,” to the 3D shape-filled surface). On optimization problem may be constructed for approximating this area with 1 capsule object. For example, the following relationship may be minimized, subject to the constraints that the end points of each capsule must lie inside of the convex hull of the tooth shape, and each least square straight-line (LSS) closet vertex from the tooth shape should not be farther than some small limit:

∑k[ωkminmDistance(vertexk,⁢capsulem)]2

In this relationship, wkis the weight for vertex vkof the original shape. For interproximal (IP, the region between adjacent teeth) area approximations:

ωk=f⁡({vertexk}y2)

This may be solved with an optimization solver, and a newly found surface may be added to the approximation, while obsolete surfaces may be removed from the approximation. The total approximation may then be refined. This process may be repeated (iterated) as much as necessary until the desired precision is achieved.

For example, in some variations, the systems and methods described herein may select a subset of vertices from the digital model (e.g., scan) of the tooth surface, and may approximate this subset of vertices with one capsule. An optimization solver may be used to minimize the distance between the capsule and the selected subset of points. If the approximation is poor (e.g., below some threshold for approximation), the set of point is not adequate, and the subset of vertices may be revised to find points within the vertices that may be approximated better, or finding new sets of points that may be approximated more closely within the desired range (e.g., another capsule may be identified to approximate the smaller subset of points). Once the initial packing of capsules has been completed, each approximating a small subset of points on the tooth, the optimization process may be repeated with some of the capsules rearranged to achieve a higher precisions. The process may stop when the maximum amount of capsules desired is reached. For example, the threshold number of capsules may be set to, e.g., 15 capsules (10 capsules, 12 capsules, 15 capsules, 20 capsules, 25 capsules, 30 capsules, 35 capsules, etc.). Alternatively, in some variations, the process may be repeated until a precision limit or threshold is reached, without limiting the number (and therefore size) of capsules. For example, a precision limit may be set to require filling of all spaces bigger than 0.001 mm. Alternatively, a combination or balance of the two (number of capsules and/or minimum precision limit) may be used, for example, increasing the number of capsules if the precision is within a predefined range.

AlthoughFIG.32A-32Billustrates an example of an entire tooth modeled using a plurality of capsules, other structures may also be modeled, including other dental structures that may be present on the tooth or associated with the tooth. For example,FIGS.33A-33Billustrate perspective views of a portion of a dental appliance (a precision wing portion3301) that has been modeled by packing with a plurality of 3D shapes (e.g. capsules). In some variations, this may be beneficial for detecting collision between the teeth and an orthodontic device, or between multiple orthodontic devices, etc.

FIG.34Aillustrates an example of a tooth having a surface (an interproximal surface) that is modeled using a plurality of capsules. InFIG.34A, the left interproximal surface3405is approximated by packing the surface with a plurality of capsules of various sizes. Other region of the tooth (e.g. crown region) are not modeled, or not modeled to the similar precision. In some variations, multiple regions associated with the same tooth may be modeled separately, such as left and right interproximal regions, crown regions, etc.FIG.34Billustrates a dental arch including a plurality of individual teeth. Each tooth is divided up into left and right sides, and in some teeth (e.g., molars, premolars) a separate middle region; the left and right regions may be modeled separately. For example, the boxed incisor3408includes a left side3410and a right side3412, shown by different shading, and similar distinctions can be made for all of the teeth.

Once one or more surfaces of the teeth have been digitally modeled by packing 3D shapes, a hierarchy of bounding boxes may be formed around all of the 3D shapes and adjacent sets of shapes for each modeled surface of each tooth. Building a hierarchy of bounding boxes may provide a rapid and efficient way to determine which capsules between two adjacent teeth may be closest to each other and/or may overlap. The use of bounding boxes, and particularly an organized hierarchy of bounding boxes, may reduce the time for finding closest pair of capsules dramatically. The bounding boxes allow the rapid determination of an approximate value of a collision/separation in space, instead of a precise one. The approximate value may be calculated as a minimal distance between all possible pairs of capsules of two shapes. For example, approximate collisions can be used in optimization process of treatment plan generation to provide a good initial guess of teeth position that fulfills almost all requirements besides some small violations of collision/space rules left due to imprecision of approximate calculations. Those violations can be resolved by switching back to precise calculations (e.g., using the capsule distance). This combination of bounding boxes and 3D shapes, allowing both rough and more precise determination of spacing, has been found to give a substantial performance boost of up to 150 or more times compared to the use of more precise collision depth/space calculations only.

The use of the hierarchy of bounding boxes, which provide approximate collision information, with the more precise collision information provided by the 3D shapes, such as capsules, particularly by increasing the number of capsules, may allow both rapid and accurate collision/spacing information.

The hierarchy of bounding boxes may be organized so that each capsule is put into a bounding box that fits it tightly. Each bounding box containing one or more capsules are considered leafs of the hierarchy. Each box from a higher level of hierarchy bounds several boxes from a lower level of hierarchy.FIG.35Aillustrates one example of a hierarchy of bounding boxes for four capsules. In this example, capsules A, B, C, D are each bound in a bounding box, forming the lowest level of the hierarchy. Bounding boxes A and B are united into bounding box AB, and bounding boxes C and D are united into bounding box CD. Finally, at the top of the hierarchy, bounding boxes AB and CD are united in bounding box ABCD.FIG.35Ashows the entire hierarchy arranged as a tree, with the boxes corresponding to individual capsules at the lowest level.

Any appropriate algorithm for construction of a hierarchy of bounding boxes can be used. Using tighter bounding boxes (e.g., having smaller volumes) may result in more efficient usage of the hierarchy in collisions computations, therefore the methods and apparatuses described herein may build a hierarchy while minimizing the volume of the resulting bounding boxes on each level of hierarchy. Each tooth may have a single hierarchy, or multiple hierarchies, e.g., corresponding to the left interproximal side and the right interproximal sides, etc. The hierarchy may be traversed to avoid calculation of distances between pairs of capsules that cannot influence the outcome value of collision/space when checking adjacent teeth for collisions. For example,FIG.36illustrates an example of a method (e.g., shown here as pseudo-code) for traversal of bounding box hierarchies to skip distance calculation between capsules that cannot influence the final value of collision/space. This method may start at the highest level and see if there is any collision (e.g., overlap) between the highest levels of the hierarchy by, e.g., measuring the distances between the largest (top level) bounding box for each adjacent tooth or both adjacent tooth regions. If there is no overlap at the top level, there is no collision at all. However, if there is a collision, then the next level down the hierarchy may be compared to determine which branches of the hierarchy include collisions; for each branch that includes a collision, the procedure may continue down to the next level/branch until the lowest level (capsule or other 3D shape) is reached; the final levels on both teeth, or regions of the teeth, therefore represent the regions that are colliding, and these regions may be examined to determine the depth (magnitude) of collision.FIG.37Aillustrates one method of analytically determining the distance between two capsules of different hierarchies. In general, the apparatuses and methods may measure the distance, d, between the cores of the 3D shapes and the minimum separation between the capsules in this example is equivalent to the shortest distance between the two line segments minus the radius of the first capsule and the radius of the second capsule.FIG.37Balso includes an example of a pseudo-code set of instructions for finding approximate distance between two shapes, such as, for example, shape A and shape B packed with capsules shown inFIGS.35A-35B. Although the examples described herein include bounding boxes, other simplified bounding geometries may be used, for example, bounding sphere or bounding capsule hierarchies may be used.

In addition to detecting the magnitude of any collision that occurs when the teeth are in a specified position, the methods and apparatuses described herein may be used to determine the velocity of any collision. In doing velocity measurements, one or both teeth may be moved very small increments (e.g., less than 0.001 mm, less than 0.01 mm, etc.) in one or more axis (x, y, z axis, roll, pitch and yaw.), and the resulting change in the overlap determined for each axis. The final velocity may be measured for each of the six axes, and/or may be combined into a single indicator (e.g., vector) sum or relationship.

During any of the processes for determining the velocity of a collision, in which the tooth may be ‘jittered’ in one or more of its axes, the closest pair of capsules in collision/space with any change in position of shape is very small. This can be used for faster calculation of gradients in optimization algorithm for determining the final position of the teeth following treatment, and for staging construction. For example, the tooth may be moved in each of the six axes (e.g., three translational axes, x, y and z, and three rotational axes: pitch, yaw and roll) by a small amount (e.g., less than 0.001 mm of translation, less than 0.01 degree of rotation, etc.). This is illustrated inFIG.40, for example, showing the axes around one tooth. The same capsules identified as colliding may therefore be re-examined following the small movements to determine the velocity of the collision. When using the solver/engine to solve for one or more treatment plan, the solver may avoid collisions between teeth. For the solver to estimate an optimal solution when planning a treatment, the solver may be provided by not just the magnitude (e.g., depth) of the collision, but also the velocity of the collision, e.g., how the collision depth reacts to small changes of position relative to the neighboring tooth. If one tooth is fixed, but the other is moved, e.g., jittered, about its original position, the same pair(s) of capsules may be used for very rapid calculations. The depth may be defined as how close the tooth is to another tooth, e.g., in mm of overlap. In some variation, the method and/or apparatus may alternatively measure the space between the two closest capsules (e.g., even when not colliding).

In use, the method of solving for the magnitude and velocity of a collision may be integrated into a method for solving for one or more treatment plans. For example, the treatment plan solver may call on the collision detector to identify the collision and rotation between each tooth. The treatment plan solver may have initially identified digital models of the patient's teeth in which one or more surfaces were modeled by 3D figures such as capsules. See, e.g.,FIGS.38and39. The patient's teeth, e.g., along the interproximal regions, may be modeled as individual teeth (or set of teeth) and the overlap3509may be determined. The teeth do not need to be re-modeled when making additional collisions determinations. The collision detector (collision engine) may measure the change in magnitude as a collision depth, and may also determine the velocity of the changing magnitude for each of a plurality of axes.

A special variant of the method is used during construction of orthodontic treatment with a non-linear optimization based algorithm. For example, to compute gradients of change of collision or space amount, every step of a non-linear optimization algorithm may compute values for thousands of small variations of teeth positions. The result of previous computations may be used to select smaller number of capsules that must be considered to find the amount of collision or space, provided the change of position was limited by a small constant bound. This additional pruning reduces computational complexity from O(N2) to O(1), and allows an increase in the number of capsules used in tooth approximation without corresponding increase of computation time, increasing the precision.

In examples in which the capsules have a planar figure (e.g., line, rectangle, etc.) in the core, and an outer surface extending a constant radius from the core in x, y and z, collisions (e.g., overlap) between the teeth may be analytically determined from the 3D shapes with high precision. These systems and methods may also be applied to just adjacent portion of the teeth (rather than the entire teeth) and may be combined with a hierarchy of bounding boxes in order to accelerate the computation, as described above.

Any of the methods and apparatuses described herein, including subcomponents or subsystems (e.g., such as system or subsystem for automatically detecting collisions between teeth, which may be referred to as collision detectors) may be configured for constructing approximated shapes of teeth by packing the surface(s) of the teeth, or in some variations, other structures (e.g., attachments, brackets, etc.) using multiple three dimensional (3D) shapes (such as capsules), as described above, and these 3D shapes (“capsules”) may be selected based on the shape(s) of the product being modeled, including teeth and/or other structures, such as retainers, attachments, etc. As describes above, in general approximation of shapes using the capsules as allows a dramatic reduction in the time necessary for collision computations which may be a bottleneck in treatment plans construction. However even if the accuracy of approximation is not high, a filling (e.g., capsule-based) technique may still be useful in eliminating remaining collisions when modeling. In some variations, the construction of high-precision approximations can result in significant time savings even without requiring a refinement of treatment plans with precise computations.

For example, in some variations topographical information about the face(s) of the teeth or other targets being modeled may be used to select the size, shape and/or position of the capsules. In some variations topological information about faces (such as curvatures) is used to find regions best suitable for approximation with single capsule. This may be accomplished by identifying one or more areas on a shape having a closed curvature; in some variations, when the capsules consists of spheres of fixed radius, or shapes based on a fixed radius, they may not efficiently approximate areas that have different curvatures.FIG.41Aillustrates one example of a pair of tooth shapes showing regions having close (closed) curvatures that may be approximated using a single capsule. InFIG.41A, each of the different regions (shown by different shading), e.g.,4101,4103, has a close curvature. Use quadric error metric to measure distance from shape to approximation. Any appropriate method may be used to determine the curvature of the surface.

Once identified, the curvature may be used to determine the shape, size and/or position of the capsules. Capsule approximations may be refined on the fly. For example information about approximation quality in different regions may be determined, stored, and used to refine approximations interactively if collision was requested in a particular (e.g., a “bad” region, or region of high error, as shown inFIG.41B). InFIG.41B, the shaded dots of different sizes show regions having approximation errors (e.g., the relative sizes of the dots4109,4109′ inFIG.41Breflect the approximation error at each dot position).

For example, described herein are methods of determining/detecting collisions as described above, in which an initial partitioning of the three-dimensional shape(s) (e.g., teeth) may be based on curvatures of the outer shape surface. Thus, the method, or any apparatus configured to perform it, may identify a face of the outer surface that is close. For each face, the method or apparatus may construct a vector with coordinates (x1, . . . , x7) where x1 . . . x3 are coordinates of center of a face, x4 . . . x6 are coordinates of vector (k1*d1+k2*d2){circumflex over ( )}n (k1, k2are principal curvatures of face, d1, d2are principal directions, and n is normal to face), and x7 is a mean curvature of a face defined as k1+k2.

A clustering algorithm may then be used with the constructed set of vectors, and the number of clusters should be equal to desired number of capsules. In this technique, the center of each cluster may be used to construct a capsule to be used by an optimization algorithm as an initial guess. A quadric error metric may be used to control approximation sticking from 3D shape; for measuring a distance between a capsule and a plane, the following definition may be used:
Distance(Capsule,Plane)=min(quadric error metric(s(t,r),Plane))

In this technique, t belongs to [0,1], s(t) is sphere with center p0+t*(p1−p0), p0 and p1 denote end points of capsule, r is radius of capsule. This metric differs from the distance from an un-oriented point p (as opposed to a plane {p, n}) to a capsule; it also takes into account the orientation of the normals, and distinguishes naturally between convex and concave regions.

As mentioned above, any of these methods may include refinement of capsules on the fly. For example, after an approximation is computed, the apparatus or method may include marking poorly approximated areas with marker (e.g., flag). A collision computation may check if any poorly approximated areas lie near a potential collision area; if so, the method or apparatus may perform a capsule construction for the affected areas (near potential collisions; other regions with a low probability of collisions may be ignored, even if poorly approximated). Newly constructed capsules may then be added to the approximation, and the collision results may be recalculated using the newly constructed capsules.

The methods described above may be used to dramatically increase the speed and/or efficiencies of these techniques. For example,FIG.41Cillustrates an example of a comparison between collision detection using capsule approximations at different levels of precision. InFIG.41C, the right side4133is an approximation of a tooth in which 70 capsules are used to approximate the tooth surface (e.g., 70 capsules per tooth), while the right side4135is an approximation using 300 capsules per tooth. The approximation using 70 capsules per tooth was over 20× faster (e.g., taking 10-15 seconds for the reconstruction) than a precise collision detection method (e.g., using a triangular mesh), while the 300 capsules per tooth was between 3×-7× faster (e.g., taking >1 minute for the reconstruction). The 70 capsules/tooth4133example may be considered a “moderate precision” technique, having a difference compared to a precise model of approximately 0.1 mm, while the 300 capsules/tooth4135example is a higher precision model, having a difference compared to a precise model of approximately 0.03 mm.

Example

An example of a method for generating an optimal partial treatment plan may include, for example, determining (in a computer processor) an initial position of each of the patient's teeth (position and orientation, in six variables) from a digital model of the patient's teeth. The digital model can be the upper jaw, lower jaw or both upper and lower jaws. The software typically divides the models into individual teeth and positions them into patients bite relationship. The steps of determining the position of the patient's teeth may be done in the same processor (or as part of the same device) that does the rest of the method (e.g., solves for the solution vector) or it may be a different, separate processor. Any of these methods may then determining a comprehensive (e.g., “optimal”) final position of the patient's teeth.

A processor performing the method may then receive product definition (e.g., number of stages to be used) specific to the patient treatment. Other product information may include: maximum allowed number of stages, whether attachments are allowed, maximum allowed root movements, crown movements and rotations, etc.

Thereafter the processor may receive preferences (e.g., interproximal reduction, attachments, tooth/teeth that don't move, etc.) specific to the patient treatment. Preferences may include: indicating which tooth/teeth are not to move, individual teeth where attachments should not be placed, arch to treat (both jaws, only lower or only upper), class correction amount and method, IPR, arch expansion, spaces, levelling preferences, etc.

The processor may then express a plurality of treatment targets of the treatment plan as numerical functions (“target functions”) based on the product definition and preferences, weight each numerical function, and sum them to form a single numerical function. This single numerical function may include a weighted sum of at least, for example: tooth position compared to the comprehensive final position of the patient's teeth, misalignment (x- and z-misalignment, alignment to arch), diastema (spaces between neighboring teeth), collisions (inter arch collisions), and length of treatment (number of stages). Thus, the single numerical function (e.g., the merit function) is a nonlinear combination of treatment targets (target functions) weighted by pre-defined coefficients. Typically, key components of the merit function are objective (independent of the comprehensive position) measurements of aesthetic concerns: misalignment between teeth, spacing between teeth, amount of overjet and amount of overbite. Components that are relative to comprehensive final position mostly describe orthodontic goals (arch form, occlusion, levelling, alignment, etc.).

The pre-defined coefficients may be set or determined empirically, e.g., by expert opinion, or may be solved. For example, starting from initial guess where weights are roughly same, setups may be prepared for cases from an existing database and reviewed. In addition, some adjustments can be made for technical reasons (i.e. to improve converging to a solution, which may be delayed if weights are inconsistent).

Constraints on tooth movements may then be expressed as numeric limits based on the product definition, preferences and comprehensive final position, including at least: the maximum velocity of tooth movement, maximum amount of collision, tooth movement limitations, staging constrains, and maximum amount of occlusion. As discussed above, other constraints may include: the maximum velocity of tooth movement, maximum amount of collision and space, tooth movement limitations, staging constrains, maximum amount of occlusion, amount of overbite, overjet, and midline position.

The single numerical function subject to the constraints on the tooth movements may then be solved (e.g., minimized) using a constrained optimization algorithm to get a solution vector and map the vector to a treatment plan. One example of a constrained optimization algorithm is the Interior Point method, including Interior Point method variations SQP and Active Set. Other methods may alternatively or also be used.

The solution vector is produced as a result of solving the constrained optimization algorithm. The optimization problem is defined as finding the values of variables x1. . . xNthat minimize merit function f0(x1. . . xN) and do not violate inequality constraints fi(x1. . . xN). Solution vector is the values of x1. . . xNthat optimization algorithm produced as an output. Variables are mapped positions teeth, for every key-frame on every tooth there are seven variables: x, y, z coordinates, angulation, inclination and rotation angles, and stage number of the key-frame. For example, x1, x2, x3, x4, x5, x6may be the initial position of molar, x7would be constant stage 0 (initial), then x8. . . x14would be position, angles and stage number of intermediate key-frame added to molar for staging, then x15. . . x21are final position of the molar and final stage number (length of treatment). Then x22. . . x43are initial, intermediate and final positions and stage numbers of pre-molar, and it continues for every tooth. There may be different number of intermediate, staging key-frames on each tooth, so 14 variables per tooth at minimum, to 42 and more variables for teeth with many staging key-frames). If multiple intermediate key-frames are present on a single tooth and their order is not fixed, each coordinate (such as angulation) of tooth at every key-frame may be calculated instead as a sum of piecewise functions parametrized by the stage number and coordinate variables. The piecewise functions may be defined so that if xi. . . xi+6variables corresponding to six coordinates at a key-frame are equal to zero, tooth movement through this key-frame is linear, which is equivalent to absence of key-frame.

FIGS.26A-26Billustrate one example of a set of key frames. Key frames are described in greater detail in U.S. Pat. Nos. 8,038,444 and 6,729,876, herein incorporated by reference in their entirety. The number of key frames used may be predetermined, or may be determined by the apparatus or method. Each tooth may have a different number of key frames.

Key frames may be used to simplify the treatment plans. For example, treatment plants may be stored as positions of key frames of every tooth. A key frame is essentially an animation of teeth movement from position at initial stage, through all key-frame positions to the position at a final stage. Thus, the treatment plan does not need to store positions for every stage. Defined positions may be at initial, final, and one or more intermediate stages that are referred to as key frames. The position of tooth on a stage that is not a key frame is interpolated between the two adjacent key frames. Thus, as mentioned above, staging, i.e., intermediate positions, of each tooth may be a linear combination of several functional component. Each component describes deviation from linear movement at a certain stage and is parameterized by six coordinate deviations and a stage number.

User-Specific Treatment Preferences

The methods and apparatuses described herein typically use treatment preferences to, in part, define the target functions (and therefore merit function) and constraints that are then used to automatically pre-calculate one or more treatment plans. Each user (e.g., dental professional) may use the same general treatment preferences when treating different patients. It would be very helpful to customize treatment plan generation (and display) to the users, particularly as the same users may worth with many patients.

For example, it would be beneficial to personalize treatment planning automation for all users (e.g., dental professionals). This may be done using domain-specific language that can be integrated into the methods and apparatuses described herein. For example, the start of any treatment (including patient consultation) may include a questionnaire or template that the user completes. The treatment planning optimization engine may use a treatment template described with a domain specific language in order to control case processing flow to create treatment according to personal needs of the user.

There may be two sources of dental professional's preferences on how to prepare treatment plans. One source of treatment preferences which may be essentially a structured input where for a set of questions, the user provides answers, where each answer is a selection from a set of predefined answers. The second source of information may be represented as a text-based comments which defines the user's personal rules to follow when preparing a treatment plan for a doctor. Domain specific language may be used to store user's non-structure input (e.g., text comments describing his treatment preferences) which may enable full automation of treatment planning as well as aggregation of rules from multiple sources (for example, structured preferences and non-structured treatment preferences).

Structured treatment preferences may cover only a small portion of users' personal treatment protocols. Instead, much of the treatment protocol details may be provided by the user in non-structured, text form. While setting up a treatment plan, a technicians uses both structured treatment preferences and non-structured treatment preferences. If this information were used manually, when a technician applies text-based user preferences, misinterpretation and inconsistency in treatment plan quality may result, and the resulting treatment plan may depend on the technician. As described herein, text-based comments expressing doctors treatment planning style may be converted into a domain-specific language (manually or automatically) and the methods or apparatus (e.g., software) may interpret this domain-specific language to automatically apply doctors preferences for treatment planning preparation.

From the users perspective, the user fills two sections of his preferences describing his treatment style, e.g., on a web site. One section may be represented as questions with predefined set of answers each, and another second may be text-form comments. The user may then saves her preferences, and both types of preferences may then be applied to cases associated with (e.g., submitted by) this user.

The user's text-based preferences may be transformed into a domain-specific language which defines clinical rules to apply for treatment planning in a formal way which also may be interpreted by Treat treatment planning software. This may initially be performed manually or semi-automatically, and may initially include manual review and checking (including checking with the user). However, once the domain-specific language is constructed for that user, it may be used without requiring manual intervention, unless modified at the user's request (e.g., when displaying the resulting treatment plans, as described herein). Each user may be associated with a rules file that may be unique to the user and may be updated independently from other users.

When case is submitted by a user (e.g., requesting a treatment plan), the user's preferences, expressed in a form of a domain-specific language, may be accessed from the stored database and aggregated with other user preferences (e.g. patient-specific target preferences or additional structured input provided by the user) and may be used to execute the fully automated treatment planning described above.

FIG.27illustrates one method of defining user-specific treatment preferences based on both structured and unstructured input. For example, inFIG.27, the method (or any apparatus configured to perform this method, which may be a treatment plan optimizing engine or treatment plan optimizing generator) may first acquire a set of textural instructions (e.g., unscripted instructions) from a user (e.g. a dental professional such as a dentist, orthodontist, etc.)2701. These may be typed or handwritten (and converted to a machine readable form) and then converted into a domain-specific language specific to the user; this represents a first set of rules (treatment preferences). As mentioned above, this step may be initially performed semi-automatically or manually to build the domain-specific language. Once built, it may be fully automatic2705.

Concurrently or sequentially, the method may acquire a set of scripted instructions from the user. The scripted instructions may comprise responses from a script of predefined choices (e.g., a survey, questionnaire, etc.)2703. The responses to the set of scripted instructions may be automatically converted into a second set of rules (treatment preferences)2707. Thereafter, the method may include accessing, by the automated treatment planning engine, the first set of treatment preferences and the second set of treatment preferences, and forming a combined set of treatment preferences from them2709. The automated treatment planning engine may then access (e.g., receive, look-up, etc.), a digital model of the patient's teeth2711, and any of the other inputs necessary to automatically generate a treatment plan for the patient's teeth using the combined set of treatment preferences the digital model of the patient's teeth, a comprehensive model of the patient's teeth and/or treatment details (e.g., product details), as already described above2713.

FIG.28illustrates another example of this. In this example, the treatment plan optimizing engine or treatment plan optimizing generator2813includes a rules aggregator2815that combines the treatment preferences from user-specific treatment preferences that are stored in a database indexed by user2805that are converted via a domain-specific language2803into a first set of treatment rules, along with the user's patient-specific treatment preferences (specific to the instant case)2811that may also be converted by the domain-specific language2819into rules, and these rules may be combined2815, then converted into treatment preferences using a language interpretation module2817. The interpretation of these rules into treatment preferences may depend in part on the product (e.g., aligner features2821), and may be provided to for determining staging2823and the optimal (e.g., comprehensive) final position2825.

Thus, a set of rules may be expressed in a domain specific languages and associated with each user in a clinical database. A module may converts structured input (e.g., answers given by a doctor on a set of questions) into additional set of rules. These rules may be combined via a rules aggregation module which combines rules from multiple sources into a single rules list. The language interpretation module may takes any of these rules files as an input and interpret it to control the flow of FiPos, Staging and Aligner Features modules in order to create a treatment plan fully automatically, as described above.

Automatic Selection Treatment Plans

The methods and apparatuses described herein may provide multiple treatment plans and may allow the user (e.g., the dentist, orthodontist, dental professions) and/or in some variations the patient, to view all or a subset of these treatment plans, and to select one or more of these plans from which a series of dental appliances to be manufactured treatment. As described above, a very large number (e.g., 12, 18, 24, 30, 36, 40, 48, 50, 55, 60, 65, 70, 75, 100, 125, etc.) of treatment plans may be generated concurrently. Ordering or organizing the treatment plans, and in particular, determining the order of which treatment plans to display and/or how the user may toggle or select between these different treatment plans may therefore be helpful.

In any of these variations, the treatment plans may be sorted or organized by assigning a weight to each treatment plan based one or more criterion. For example, if24different treatment plans are generated, it would be helpful to automatically order the treatment plans using one or more criterion and to display them in that order. For example, the treatment plans may be ordered (assigned weights) and displayed based how comprehensive they are. The degree of comprehensiveness may be based on, for example, how closely the predicted final position of the tooth resembles the ideal final position of the patient's teeth (or an arbitrary final position) that is calculated as part of the procedure for generating the multiple treatment plans described above.

In some variations, different categories of treatment plans may be displayed concurrently, e.g., the most comprehensive treatment plans among treatment plans having a first characteristic (such as a those treatment plans limited to a first number of stages, e.g., 16 stages) may be displayed alongside the most comprehensive treatment plans having a second characteristic (such as those treatment plans limited to a second number of stages, e.g., 24 stages, or unlimited stages). The methods and systems described herein may determine how comprehensive each treatment plan is by comparing to the ideal final position and/or by applying ranking logic in which the each of one or more characteristics (also referred to herein as criterion) are used to determine the weighting. For example, treatment plans with interproximal reduction (IPR) may be weighted more than plans without IPR; treatments plans with extraction may be weighted higher; treatment plans with all attachments (e.g., anterior and posterior) may be weighted higher than plans without attachments, plans with only anterior attachments may be ranked higher than those with only posterior attachments, treatment plans including both upper and lower arch may be ranked higher thank those with only one of the dental arches; upper arch only treatment plans may be ranked higher than lower arch only, etc. Each of these characteristics may provide a number of points (weights) and the final ranking may be determined by the sum of these points for each treatment plan.

In addition to, or instead of, ordering the plurality of treatment plans based on the comprehensiveness of each treatment plan, the methods and apparatuses described herein may order the treatment plans based on one or more alternative or additional criterion, such as: the duration of the treatment plan, the number of stages, the amount of tooth movement achieved, etc. The criterion may be user selected or automatically selected. In some variations, the criterion may include, for example, a prediction of a user preference; the user's preference may be determined by machine learning, and may be specific to the user (e.g., based on prior/past preferences or selections for that user) or it may be generic.

For example, in any of these variations, the system may select two of the sorted treatment plans for side-by-side (concurrent) display; in some variations along with the original tooth position and/or the ideal tooth position calculated. As mentioned, the system may select the highest-ranked treatment plans within two (or more) categories for concurrent display. The ranked treatment plans may be displayed in an initial user interface screen, from which the user may then toggle between other treatment plans using one or more controls on the user interface, as described herein. In some variations, the system selects two of the most comprehensive treatment plans and show them to the user in an initial display for user review (e.g., using a treatment review system or sub-system). The system may weight each treatment plan based on the one or more criterion. For example, the system may weights of each treatment plan based on attributes such as IPR, use of attachments (and type of attachments, and/or number of attachments, and/or where attachments are used), presence or single arch or dual arch treatment for treatment plan, etc. As mentioned above, these criterion may also be used to select categories for concurrent display. The apparatus may sort and return the most comprehensive for the case.

FIG.42illustrates one example of a display showing side-by-side (concurrent) display of the sorted treatment plans (sorted for comprehensiveness based, e.g., clinical efficiency using ranked criterion). In this example, the first display screen shows the final tooth positon for plans with highest ranking in each of two categories: a first product, “Invisalign GO Plus” and a second category “Invisalign Go” product). A user can start review them without spending time to browse plans and finding best ones. Thus, the system and method may default to showing the highest-ranked treatment plans first, where treatment plans are ranked as described herein. InFIG.42, the left side image4201shows the initial position of the patient's teeth. The right-side images may be images of the final tooth position for the highest-ranked treatment programs in two categories. For example, the middle image4203may the highest-ranked treatment program among those qualifying as the first product (“Invisalign GO Plus”, e.g. limited to 12 or fewer stages). The right-side image4205may be the highest-ranked treatment program among those qualifying as the second product (e.g., “Invisalign GO” product, limited to 20 or fewer stages). This display view may be referred to as a multiple cards view. The display may also indicate features used as part of the calculations done on each treatment plan, such as the use/type of attachments4211, the use/non-use of IPR4201, the movement of both arches4213, the product used4215, etc. The display may also indicate the number of stages in the treatment plan4217. As will be described below, in some variations these indicators may be selectable controls, e.g., drop-down menus, buttons, etc., that may allow the user to toggle between treatment plans.

In practice, when generating the one or more treatment plans, the system may set up how to rank the treatment plans for initial display, e.g., in the multiple cards display. For example, the system may look at all or a subset of the parameters used when calculating the multiple different treatment plans, including but not limited to: information about IPR (e.g., IPR used/IPR not used); information about attachments set (e.g., attachments: Yes/attachments: Posteriors only/attachments: No); arches to treat (single arch treatment/dual arch treatment); treatment type (“Invisalign Go”/“Invisalign Go Plus”), etc.

In some variations, if only one Product Type is available for the Doctor, then only one Treatment Plan shall be shown in the Multiple Cards View by default. Alternatively, in some variations, the multiple cards display may be used to display single arch/both arch views or other parameters. For single arch treatments submitted by the user, the most comprehensive single arch treatment plan may be selected and shown in the Multiple Cards View for each available product type.

As mentioned above, the each of the generated treatment plans may be ranked (e.g., scored). For example, table 1 (FIG.43A) illustrates one example of a ranking of priorities that may be used to pick the most comprehensive single arch treatment plan within one treatment type to be shown to the user. In this example, lower numbers are higher ranked (e.g.,1is the highest priority, 11 is the lowest priority). The simplified table ofFIG.43Ashows the relationship between two categories (IPR and attachments) that may have two or more different states; other categories may be included, adding multiple dimensions.FIG.43Bis a table illustrating another example of a set of rankings for dual arch treatment; the same categories apply. Thus, when determining a ranking score for each treatment plan, the system may use a look-up table (or tables) similar to the tables shown inFIGS.43A-43B, or it may apply a scoring system in which a particular number of “points” may be assigned for each parameter state (though note that this may result in ‘ties’ that may be permitted or reconciled using second set of preferences).

In the example of scoring usingFIGS.43A and43B, when determining the initial display, the treatment plan with the lowest value score may be displayed. In variations in which one or more option are not available to the user (e.g., only one Product Type is available for the doctor, the user is not able/willing to provide IPR, etc.) then treatment plans, if generated, may be scored lower or removed. In some instances, even if not selected by the user (if, for example, the user indicates “no IPR”), treatment plans including these options may still be generated, so that the user can compare the use/non-use of these options directly.

From the initial view, the user may select one or more of the treatment plans for side-by-side comparison with other selected treatment plans and may begin to look though other (lower ranked) treatment plans by controlling the options/criterion. For example, the screen may include a “compare” or “save” control (e.g., button) that may allow the user to store this case for analysis. In some variations, a control may be used to move a selected treatment plan to one side of the display (e.g., in some variations replacing the initial view of the patient's teeth) so that it can be directly compared to other treatment plans.

In addition to directly toggling between options on the user interface, a control may also be provided to allow the user to see the next-ranked treatment plan (e.g., a button, or other control on the user interface, etc.). For example, selecting a “compare” button in the Multiple Cards view may be used for showing, in a dual arch treatment case, the next treatment plan according to the priorities scaling/ranking described above, such as in Table 2 ofFIG.43B. Clicking the same control (e.g., a “compare” button in the Multiple Cards view) for the single arch treatment case, will pick the next treatment plan according priorities described in both Tables 1 and 2 (e.g.,FIGS.43A and43B). In one example, both treatment types are available for the user (e.g., Invisalign Go and Invisalign Go Plus), then clicking on “Compare” button in the Multiple Cards view, the system may pick the most comprehensive treatment plan with the Product Type which is absent in that view usingFIG.43Afor the single arch treatments and using, e.g., Table 2 for the Dual Arch treatments. In some variations, the “Invisalign Go Plus” program may generate a treatment plan that can be shown in the Multiple Cards view (e.g., on the left) by default if both treatment types are shown. In some variations the Invisalign Go Treatment Plan may be shown at the right in the Multiple Cards view by default (e.g., if both treatment types are present).

Treatment Plan Filters

As discussed above, any of the methods and apparatuses described herein may be configured to display one or more treatment plans, typically by showing one or more of the model of the patient's dental arch(es) at one or more stages in the treatment plan, and allowing the user to toggle or switch between treatment plans by changing which parameters or constraints specified when generating the treatment plans. Thus, a user may select, in real-time, an appropriate treatment plan by using filters, toggles, or switches against the clinical parameters, such as one or more of: interproximal reduction (No IPR/No, IPR), Attachments (all attachments, No Attachments, anterior only attachments, posterior only attachments, etc.), etc. These controls may be referred to as clinical filters and the user may select the most appropriate treatment plan for the particular patient using these clinical filters to rapidly compare treatment plans. Using clinical filters may also allow the user to fine-tune a selected treatment plan. For example, in some variations the user may select another value for IPR or attachments using the filters and may then immediately submit the modified treatment plan to generate a new family of modified treatment plans that may be viewed immediately or shortly thereafter.

Thus, by toggling between treatment plans, the user may automatically and quickly browse between multiple treatment plans by choosing key features that can affects final position, such as the use and placement of attachments, IPRs, treatment of one or both arches, etc. Each filter can display one or more notification or tip if the feature is not available for a particular case.

For example,FIG.44is a mock-up of a multi-card view that shows three panels. The first panel shows an image (3D model from a scan) of the patient's current teeth4401. The middle panel shows an image of the patient's teeth from a first treatment plan4403(e.g., a treatment plan having 9 stages, using the constraints of the “Invisalign Go Plus” product, which has a limited number of stages permitted, in which IPR was not used, no attachments were used, and aligners are used on both arches). Similarly, the third panel shows an image of the patient's teeth from a second treatment plan4405(e.g., a treatment plan having 11 stages, using the constrains of the “Invisalign Go Plus” product, in which IPR was not used, but posterior only attachments is being selected by a user using the control or filter, shown here as a button on the user interface that pulls out a drop-down menu allowing the user to specify which type of attachments are use (e.g., no attachments, yes attachments or posterior only attachments); inFIG.44, the user is preparing to select “attachments posterior only” to switch the third card to display this variation

In general the displays showing the initial malocclusion4401and the different treatment plans4403and4405may show a flat or static view of the teeth based on the simulated movement per the treatment plan; alternatively an animation may be used, showing tooth movement across multiple stages of treatment. In some variations, the stage shown may be the final stage (showing all movement); other stages may also be shown. In some variations the 3D model showing the tooth position may be rotated (or may rotate automatically) to show different perspectives.

As mentioned above, a filter may indicate one or more notification or tip if the feature is not available for a particular case. For example,FIG.45illustrates a display similar to that shown inFIG.44, showing side-by-side comparisons of the original tooth positions, and two treatment plans. In this example, although the display includes an indicator/control the number of arches (e.g., both arches, single arch) only treatment plans with a single arch were generated, and therefore if the user attempts to switch to view ‘single arch’ treatment plans, as shown in the middle image, a notification4505indicating that only dual treatment is available may be provided. In some variations the indicator may be grayed out, preventing it from being selected.

In general, any of these displays may also include an indication of the cost or price associated with the treatment plan. For example, one of the filters may allow the doctor to compare two different product types having different price. Higher price products may have, for example, more stages in the treatment and have a wider range for clinical conditions. Thus, in any of these examples, the doctor may use filters to provide an overview of what treatments (e.g., what treatment outcomes) may be best for the patient and which may be automatically suggested by the system, as described above, for a particular patient. In some varaitoins, the doctor can use these filters to review a particular clinical feature usage (e.g., comparing one plan with IPR to another plan without IPR, etc.) and compare results. The use of filters may also allow a user to see clinical details for the selected plan.

Filters may also be applied when reviewing a single plan in greater detail, as illustrated inFIG.46. This view may be referred to as a “single treatment plan” view (STP view). In contrast, the veiws shown inFIGS.44and45may be referred to as “multiple treatment plan views” (MTP views). In the example shown inFIG.46, the same controls (e.g., configured as filters) may be included; in addition, the user may select which stage4603to review or to animate between them. In addition, the user interface may include one or more controls for modifying the treatment plan4613. For example, the user may select ‘modify” and may use a tool to add/remove attachments4607and/or pontics, move the attachment, inicate IPR4605, etc. Finally, if the treatment plan looks good, the user may indicate approval4615.

In general, the user may also switch between multiple treatment plan views and single treatment plan views. For example,FIG.47shows another example of a multiple treatment plan view similar to that described above, showing a side-by-side comparison between two (or more) treatment plans, as well as the patient's original tooth configuration (“initial malocclusion”). The MTP view may show essential high-level information about the projected outcomes of the multiple alternative treatments and initial malocclusion. In contrast, the STP view may show how to achieve the selected treatment plan. Switching between these different views may help the user review the selected plan(s) and maximized to whole screen. InFIG.47, the user may select one of the treatment plans displayed by actuating the control (shown as a button4705,4705′ labeled “view” on the user interface). To open a Single Treatment Plan view (also referred to herein as a Single Card View) from a Multiple Cards (multiple treatment plan view), the user may select this control as shown inFIG.47. This may open up the single treatment plan view of that treatment plan, as shown inFIG.48. The STP may include features not in the MPT display, such as, for example: play staging, free form commenting, editing/modification of the treatment plan, etc. The user may also switch back to the multiple view by, for example, selecting a control4805for MTP, or “back”.

The single treatment plan display (e.g., user interface) may allow the user to review staging, features available on each stage of the treatment, and teeth position on each stage. As shown inFIG.49, in some variations the STP view may allow a user to approve the selected plan and send it to manufacturing or to add free form comments4905, asking the manufacturing technician to modify (e.g., improve or change) anything in this treatment plan and send the treatment plan(s) back to the technician for a treatment plan update4907, which may be manually, automatically or semi-automatically performed. In some variations, the user may view details for any plan in a MTP view by clicking on a “view” control (e.g., button). In some variatoins, the STP view may allow the doctor to see detailed staging info at the bottom of the screen, such as: treatment length for upper and lower arches, what type of aligners will be manufactured for each stage (active or passive), overcorrection stages if they are present for the treatment, animated controls to play/pause treatment animation, etc.

In any of these views, tools (e.g., on the toolbar) may be used to allow the user to review and/or modify features on any stage (attachemnts, IPRs, pontics, etc.), as discussed above in reference toFIG.46. For example, the user may click on an “approve” control (e.g., button) to send the selected treatment plan directly to manufacturing. Alternatively, clicking on a “modify” control (e.g., buton) may add/edit free form comments and send the case to a technician for an update after actuating a “submit” control4907.

Any of the methods (including user interfaces) described herein may be implemented as software, hardware or firmware, and may be described as a non-transitory computer-readable storage medium storing a set of instructions capable of being executed by a processor (e.g., computer, tablet, smartphone, etc.), that when executed by the processor causes the processor to control perform any of the steps, including but not limited to: displaying, communicating with the user, analyzing, modifying parameters (including timing, frequency, intensity, etc.), determining, alerting, or the like.

When a feature or element is herein referred to as being “on” another feature or element, it can be directly on the other feature or element or intervening features and/or elements may also be present. In contrast, when a feature or element is referred to as being “directly on” another feature or element, there are no intervening features or elements present. It will also be understood that, when a feature or element is referred to as being “connected”, “attached” or “coupled” to another feature or element, it can be directly connected, attached or coupled to the other feature or element or intervening features or elements may be present. In contrast, when a feature or element is referred to as being “directly connected”, “directly attached” or “directly coupled” to another feature or element, there are no intervening features or elements present. Although described or shown with respect to one embodiment, the features and elements so described or shown can apply to other embodiments. It will also be appreciated by those of skill in the art that references to a structure or feature that is disposed “adjacent” another feature may have portions that overlap or underlie the adjacent feature.

Terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. For example, as used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items and may be abbreviated as “/”.

Spatially relative terms, such as “under”, “below”, “lower”, “over”, “upper” and the like, may be used herein for ease of description to describe one element or feature's relationship to another element(s) or feature(s) as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if a device in the figures is inverted, elements described as “under” or “beneath” other elements or features would then be oriented “over” the other elements or features. Thus, the exemplary term “under” can encompass both an orientation of over and under. The device may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly. Similarly, the terms “upwardly”, “downwardly”, “vertical”, “horizontal” and the like are used herein for the purpose of explanation only unless specifically indicated otherwise.

Although the terms “first” and “second” may be used herein to describe various features/elements (including steps), these features/elements should not be limited by these terms, unless the context indicates otherwise. These terms may be used to distinguish one feature/element from another feature/element. Thus, a first feature/element discussed below could be termed a second feature/element, and similarly, a second feature/element discussed below could be termed a first feature/element without departing from the teachings of the present invention.

Throughout this specification and the claims which follow, unless the context requires otherwise, the word “comprise”, and variations such as “comprises” and “comprising” means various components can be co-jointly employed in the methods and articles (e.g., compositions and apparatuses including device and methods). For example, the term “comprising” will be understood to imply the inclusion of any stated elements or steps but not the exclusion of any other elements or steps.

In general, any of the apparatuses and methods described herein should be understood to be inclusive, but all or a sub-set of the components and/or steps may alternatively be exclusive, and may be expressed as “consisting of” or alternatively “consisting essentially of” the various components, steps, sub-components or sub-steps.

As used herein in the specification and claims, including as used in the examples and unless otherwise expressly specified, all numbers may be read as if prefaced by the word “about” or “approximately,” even if the term does not expressly appear. The phrase “about” or “approximately” may be used when describing magnitude and/or position to indicate that the value and/or position described is within a reasonable expected range of values and/or positions. For example, a numeric value may have a value that is +/−0.1% of the stated value (or range of values), +/−1% of the stated value (or range of values), +/−2% of the stated value (or range of values), +/−5% of the stated value (or range of values), +/−10% of the stated value (or range of values), etc. Any numerical values given herein should also be understood to include about or approximately that value, unless the context indicates otherwise. For example, if the value “10” is disclosed, then “about 10” is also disclosed. Any numerical range recited herein is intended to include all sub-ranges subsumed therein. It is also understood that when a value is disclosed that “less than or equal to” the value, “greater than or equal to the value” and possible ranges between values are also disclosed, as appropriately understood by the skilled artisan. For example, if the value “X” is disclosed the “less than or equal to X” as well as “greater than or equal to X” (e.g., where X is a numerical value) is also disclosed. It is also understood that the throughout the application, data is provided in a number of different formats, and that this data, represents endpoints and starting points, and ranges for any combination of the data points. For example, if a particular data point “10” and a particular data point “15” are disclosed, it is understood that greater than, greater than or equal to, less than, less than or equal to, and equal to 10 and 15 are considered disclosed as well as between 10 and 15. It is also understood that each unit between two particular units are also disclosed. For example, if10and15are disclosed, then 11, 12, 13, and 14 are also disclosed.

Although various illustrative embodiments are described above, any of a number of changes may be made to various embodiments without departing from the scope of the invention as described by the claims. For example, the order in which various described method steps are performed may often be changed in alternative embodiments, and in other alternative embodiments one or more method steps may be skipped altogether. Optional features of various device and system embodiments may be included in some embodiments and not in others. Therefore, the foregoing description is provided primarily for exemplary purposes and should not be interpreted to limit the scope of the invention as it is set forth in the claims.

The examples and illustrations included herein show, by way of illustration and not of limitation, specific embodiments in which the subject matter may be practiced. As mentioned, other embodiments may be utilized and derived there from, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. Such embodiments of the inventive subject matter may be referred to herein individually or collectively by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept, if more than one is, in fact, disclosed. Thus, although specific embodiments have been illustrated and described herein, any arrangement calculated to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description.