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Patent US7123767 - Manipulating a digital dentition model to form models of individual ... - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsA programmed computer is used to create a digital model of an individual component of a patient's dentition. The computer obtains a 3D digital mode of the patient's dentition, identifies points in the dentition model that lie on an inter-proximal margin between adjacent teeth in the patient's dentition,...http://www.google.com/patents/US7123767?utm_source=gb-gplus-sharePatent US7123767 - Manipulating a digital dentition model to form models of individual dentition componentsAdvanced Patent SearchPublication numberUS7123767 B2Publication typeGrantApplication numberUS 10/271,665Publication dateOct 17, 2006Filing dateOct 15, 2002Priority dateJun 20, 1997Fee statusPaidAlso published asCA2346256A1, EP1119312A1, EP1119312A4, EP1119312B1, US6409504, US7110594, US20020037489, US20020102009, US20030039389, WO2000019935A1, WO2000019935A9Publication number10271665, 271665, US 7123767 B2, US 7123767B2, US-B2-7123767, US7123767 B2, US7123767B2InventorsTimothy N. Jones, Muhammad Chishti, Huafeng Wen, Gregory P. BalaOriginal AssigneeAlign Technology, Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (101), Non-Patent Citations (99), Referenced by (14), Classifications (18), Legal Events (2) External Links: USPTO, USPTO Assignment, EspacenetManipulating a digital dentition model to form models of individual dentition componentsUS 7123767 B2Abstract A programmed computer is used to create a digital model of an individual component of a patient's dentition. The computer obtains a 3D digital mode of the patient's dentition, identifies points in the dentition model that lie on an inter-proximal margin between adjacent teeth in the patient's dentition, and uses the identified points to create a cutting surface that separates portions of the dentition model representing the adjacent teeth.
CROSS-REFERENCES TO RELATED APPLICATIONS This application is a continuation of U.S. patent application Ser. No. 10/099,310, filed Mar. 12, 2002, which was a continuation of U.S. patent application Ser. No. 09/311,941, filed May 14, 1999, now U.S. Pat. No. 6,409,504, which was continuation-in-part of U.S. patent application Ser. No. 09/264,547, filed on Mar. 8, 1999 now U.S. Pat. No. 7,063,532, which was a continuation-in-part of U.S. patent application Ser. No. 09/169,276, filed on Oct. 8, 1998, (now abandoned) which claimed priority from PCT application PCT/US98/12861 (WO98/58596 published 30 Dec. 1998), filed on Jun. 19, 1998, which claimed priority from U.S. patent application Ser. No. 08/947,080, filed on Oct. 8, 1997, now U.S. Pat. No. 5,975,893, which claimed priority from U.S. provisional application 60/050,342, filed on Jun. 20, 1997, the full disclosures of which are incorporated herein by reference.
BACKGROUND OF THE INVENTION The invention relates to the fields of computer-assisted dentistry and orthodontics. Two-dimensional (2D) and three-dimensional (3D) digital image technology has recently been tapped as a tool to assist in dental and orthodontic treatment. Many treatment providers use some form of digital image technology to study the dentitions of patients. U.S. patent application Ser. No. 09/169,276 describes the use of 2D and 3D image data in forming a digital model of a patient's dentition, including models of individual dentition components. Such models are useful, among other things, in developing an orthodontic treatment plan for the patient, as well as in creating one or more orthodontic appliances to implement the treatment plan.
BRIEF SUMMARY OF THE INVENTION The inventors have developed several computer-automated techniques for subdividing, or segmenting, a digital dentition model into models of individual dentition components. These dentition components include, but are not limited to, tooth crowns, tooth roots, and gingival regions. The segmentation techniques include both human-assisted and fully-automated techniques. Some of the human-assisted techniques allow a human user to provide �algorithmic hints� by identifying certain features in the digital dentition model. The identified features then serve as a basis for automated segmentation. Some techniques act on a volumetric 3D image model, or �voxel representation,� of the dentition, and other techniques act on a geometric 3D model, or �geometric representation.�
BRIEF DESCRIPTION OF THE DRAWINGS FIGS. 1A, 1B, and 2 are partial views of a dentition model as displayed on a computer monitor and segmented with a human-operated saw tool.
FIGS. 28, 29, 30 and 31 are flowcharts for the techniques of FIGS. 25, 26, and 27A�C.
DETAILED DESCRIPTION OF THE INVENTION U.S. patent application Ser. No. 09/169,276 describes techniques for generating a 3D digital data set that contains a model of a patient's dentition, including the crowns and roots of the patient's teeth as well as the surrounding gum tissue. One such technique involves creating a physical model of the dentition from a material such as plaster and then digitally imaging the model with a laser scanner or a destructive scanning system. These techniques are used to produce a digital volumetric 3D model (�volume element representation� or �voxel representation�) of the dentition model, and/or a digital geometric 3D surface model (�geometric model�) of the dentition. The computer-implemented techniques described below act on one or both of these types of 3D dentition models.
Orienting the Digital Dentition Model. FIGS. 25, 26, 27A�C and 28 illustrate several techniques used by the computer to orient the digital dentition model 500 properly. The computer first obtains a digital model of the dentition using one of the techniques described above (step 700). The computer then locates the model's z-axis 502, which in the depicted example extends from the base of the model toward the roof of the patient's mouth and is normal to the dentition's occlusal plane (step 702). The computer then locates the model's y-axis 504, which in the depicted example extends from an area lying within the dental arch toward the patient's front teeth (step 704). Using the right-hand rule, the computer then defines the model's x-axis 506 to extend from an area lying within the dental arch toward the teeth on the right side of the patient's mouth (step 706). The occlusal plane is a plane that is pierced by all of the cusps of the patient's teeth when the patient's mandibles interdigitate. Techniques for identifying the occlusal plane include receiving user input identifying the location of the plane and conducting a fully-automated analysis of the dentition model.
FIGS. 25, 26, and 29 show one technique for identifying the z-axis 502. The computer first identifies the dentition model 500 in the 3D data set (step 710). For 3D geometric data, identifying the dentition model is simply a matter of locating the geometric surfaces. For 3D volumetric data, identifying the dentition model involves distinguishing the lighter voxels, which represent the dentition model, from the darker voxels, which represent the background. The computer then fits an Oriented Bounding Box (�OBB�) 510 around the dentition model 500 using a conventional OBB fitting technique (step 712). The dimension in which the OBB 510 has its smallest thickness TMIN is the dimension in which the z-axis 502 extends (step 714).
Segmenting the Digital Dentition Model Into Individual Component Models. Some computer-implemented techniques for segmenting a 3D dentition model into models of individual dentition components require a substantial amount of human interaction with the computer. One such technique, which is shown in FIGS. 1A, 1B, and 2, provides a graphical user interface with a feature that imitates a conventional saw, allowing the user to identify components to be cut away from the dentition model 100. The graphical user interface provides a rendered 3D image 100 of the dentition model, either at one or more static views from predetermined positions, as shown in FIGS. 1A and 1B, or in a �full 3D� mode that allows the user to alter the viewing angle, as shown in FIG. 2. The saw tool is implemented as a set of mathematical control points 102, represented graphically on the rendered image 100, which define a 3D cutting surface 104 that intersects the volumetric or geometric dentition model. The computer subdivides the data elements in the dentition model by performing a surface intersection operation between the 3D cutting surface 104 and the dentition model. The user sets the locations of the mathematical control points, and thus the geometry and position of the 3D cutting surface, by manipulating the control points in the graphical display with an input device, such as a mouse. The computer provides a visual representation 104 of the cutting surface on the display to assist the user in fitting the surface around the individual component to be separated. Once the intersection operation is complete, the computer creates a model of the individual component using the newly segmented data elements.
FIG. 5 describes a particular technique for forming a skeleton in the dentition model. The computer first identifies the voxels in the dentition model that represent the tooth surfaces (step 130). For a voxel representation that is created from a physical model embedded in a sharply contrasting material, identifying the tooth surfaces is as simple as identifying the voxels at which sharp changes in image value occur, as described in U.S. patent application Ser. No. 09/169,276. The computer then calculates, for each voxel in the model, a distance measure indicating the physical distance between the voxel and the nearest tooth surface (step 132). The computer identifies the voxels with the largest distance measures and labels each of these voxels as forming a portion of the skeleton (step 134). Feature skeleton analysis techniques are described in more detail in the following publications: (1) Gagvani and Silver, �Parameter Controlled Skeletons for 3D Visualization,� Proceedings of the IEEE Visualization Conference (1997); (2) Bertrand, �A Parallel Thinning Algorithm for Medial Surfaces,� Pattern Recognition Letters, v. 16, pp. 979�986 (1995); (3) Mukherjee, Chatterji, and Das, �Thinning of 3-D Images Using the Safe Point Thinning Algorithm (SPTA),� Pattern Recognition Letters, v. 10, pp. 167�173 (1989); (4) Niblack, Gibbons, and Capson, �Generating Skeletons and Centerlines from the Distance Transform,� CVGIP: Graphical Models and Image Processing, v. 54, n. 5, pp. 420�437 (1992).
FIGS. 7A and 7B illustrate another technique for identifying and segmenting individual teeth in the dentition model. This technique, called �2D slice analysis,� involves dividing the voxel representation of the dentition model into a series of parallel 2D planes 160, or slices, that are each one voxel thick and that are roughly parallel to the dentition's occlusal plane, which is roughly normal to the model's z-axis. Each of the 2D slices 160 includes a 2D cross section 162 of the dentition, the surface 164 of which represents the lingual and buccal surfaces of the patient's teeth and/or gums. The computer inspects the cross section 162 in each 2D slice 160 to identify voxels that approximate the locations of the interproximal margins 166 between the teeth. These voxels lie at the tips of cusps 165 in the 2D cross-sectional surface 164. The computer then uses the identified voxels to create 3D surfaces 168 intersecting the dentition model at these locations. The computer segments the dentition model along these intersecting surfaces 168 to create individual tooth models.
Automated segmentation is enhanced through a technique known as �seed cusp detection.� The term �seed cusp� refers to a location at which an interproximal margin between adjacent teeth meets the patient's gum tissue. In a volumetric representation of the patient's dentition, a seed cusp for a particular interproximal margin is found at the cusp voxel that lies closest to the gum line. By applying the seed cusp detection technique to the 2D slice analysis, the computer is able to identify all of the seed cusp voxels in the 3D model automatically.
FIGS. 32, 33, and 34 illustrate a human-assisted technique, known as �neighborhood-filtered seed cusp detection,� for detecting seed cusps in the digital dentition model. This technique allows a human operator to scroll through 2D image slices on a video display and identify the locations of the seed cusps for each of the interproximal margins. The computer displays the 2D slices (step 750), and the operator searches the 2D slices to determine, for each adjacent pair of teeth, which slice 550 most likely contains the seed cusps for the corresponding interproximal margin. Using an input device such as a mouse or an electronic pen, the user marks the points 552, 554 in the slice 550 that appear to represent the seed cusps (step 752). With this human guidance, the computer automatically identifies two voxels in the slice as the seed cusps.
FIGS. 12, 13, and 14 illustrate a technique, known as �neighborhood-filtered cusp detection,� by which the computer focuses its search for cusps on one 2D slice to neighborhoods 244, 246 of voxels defined by a pair of previously detected cusp voxels 240, 242 on another 2D slice. This technique is similar to the neighborhood-filtered seed cusp detection technique described above.
FIGS. 15 and 16 illustrate another technique, known as �arch curve fitting,� for identifying interproximal margins between teeth in the dentition. The arch curve fitting technique, which also applies to 2D cross-sectional slices of the dentition, involves the creation of a curve 260 that fits among the voxels on the 2D cross-sectional surface 262 of the dentition arch 264. A series of closely spaced line segments 268, each bounded by the cross-sectional surface 268, are formed along the curve 260, roughly perpendicular to the curve 260, throughout the 2D cross section 264. In general, the shortest of these line segments 268 lie on or near the interproximal margins; thus computer identifies the cusps that define the interproximal margins by determining the relative lengths of the line segments 268.
FIGS. 19A, 19B and 20 illustrate an alternative technique for creating 3D surfaces that approximate the geometries and locations of the interproximal margins in the patient's dentition. This technique involves the creation of 2D planes that intersect the 3D dentition model at locations that approximate the interproximal margins. In general, the computer defines a series of planes, beginning with an initial plane 330 at one end 331 of the arch 332, that are roughly perpendicular to the occlusal plane of the dentition model (�vertical� planes). Each plane intersects the dentition model to form a 2D cross section 334. If the planes are spaced sufficiently close to each other, the planes with the smallest cross-sectional areas approximate the locations of the interproximal margins in the dentition. The computer locates the interproximal regions more precisely by rotating each plane about two orthogonal axes 336, 338 until the plane reaches the orientation that yields the smallest possible cross-sectional area.
In one implementation of this technique, the computer first identifies one end of the arch in the dentition model (step 340). The computer then creates a vertical plane 330 through the arch near this end (step 342) and identifies the center point 331 of the plane 330 (step 344). The computer then selects a voxel located a predetermined distance from the center point (step 345) and creates a second plane 333 that is parallel to the initial plane and that includes the selected voxel (step 346). The computer calculates the midpoint of the second plane (step 348) and rotates the second plane about two orthogonal axes that intersect at the midpoint (step 350). The computer stops rotating the plane upon finding the orientation that yields the minimum cross-sectional area. In some cases, the computer limits the plane to a predetermined amount of rotation (e.g., �10□ about each axis). The computer then selects a voxel located a particular distance from the midpoint of the second plane (step 352) and creates a third plane that is parallel to the second plane and that includes the selected voxel (step 354). The computer calculates the midpoint of the third plane (step 356) and rotates the plane to the orientation that yields the smallest possible cross-sectional area (step 357). The computer continues adding and rotating planes in this manner until the other end of the arch is reached (step 358). The computer identifies the planes at which local minima in cross-sectional area occur and labels these planes as �interproximal planes,� which approximate the locations of the interproximal margins (step 360).
FIGS. 35A�35F illustrate another technique for separating teeth from gingival tissue in the dentition model. This technique is a human-assisted technique in which the computer displays an image of the dentition model (step 760) and allows a human operator to identify, for each tooth, the gingival margin, or gum line 600, encircling the tooth crown 602 (step 762). Some applications of this technique involve displaying a 3D volumetric image of the dentition model and allowing the user to select, with an input device such as a mouse, the voxels that define the gingival line 600 around each tooth crown 602. The computer then uses the identified gingival line to model the tooth roots and to create a cutting surface that separates the tooth, including the root model, from the gingival tissue 604.
FIGS. 37A�C and 38 illustrate another human-assisted technique for separating teeth from gingival tissue in the dentition model. This technique involves displaying an image of the dentition model to a human operator (step 790) and allowing the operator to trace the gingival lines 620, 622 on the buccal and lingual sides of the dental arch (step 792). This produces two 3D curves 624, 626 representing the gingival lines 620, 622 on the buccal and lingual surfaces. The computer uses these curves 624, 626 to create a 3D cutting surface 628 that separates the tooth crowns 630, 632 from the gingival tissue 634 in the dentition model (step 794). The cutting surface 628 is roughly parallel to the occlusal surface of the tooth crowns 630, 632.
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