Patent ID: 12249099

DETAILED DESCRIPTION

It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example or embodiment, certain acts or events of any of the processes or methods described herein may be performed in a different sequence, and/or may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the disclosed techniques according to different embodiments of the present disclosure). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a computing device and/or a medical device.

In one or more examples, the described methods, processes, and techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Alternatively or additionally, functions may be implemented using machine learning models, neural networks, artificial neural networks, or combinations thereof (alone or in combination with instructions). Computer-readable media may include non-transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

Instructions or algorithms may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors (e.g., Intel Core i3, i5, i7, or i9 processors; Intel Celeron processors; Intel Xeon processors; Intel Pentium processors; AMD Ryzen processors; AMD Athlon processors; AMD Phenom processors; Apple A10 or 10X Fusion processors; Apple A11, A12, A12X, A12Z, or A13 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000-series processors, AMD Radeon RX 6000-series processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

Before any embodiments of the disclosure are explained in detail, it is to be understood that the disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Further, the present disclosure may use examples to illustrate one or more aspects thereof. Unless explicitly stated otherwise, the use or listing of one or more examples (which may be denoted by “for example,” “by way of example,” “e.g.,” “such as,” or similar language) is not intended to and does not limit the scope of the present disclosure.

The terms proximal and distal are used in this disclosure with their conventional medical meanings, proximal being closer to the operator or user of the system, and further from the region of surgical interest in or on the patient, and distal being closer to the region of surgical interest in or on the patient, and further from the operator or user of the system.

Navigation systems may be used to provide navigation for a surgeon or a robotic system during a surgical procedure. Such systems may provide navigation relative to, for example, a preoperative image (e.g., a magnetic resonance image (MRI) or computed tomography (CT) image) depicting one or more anatomical elements. However, during a surgical procedure, if the one or more anatomical elements move or shift, then the navigation system may no longer be accurate and may require updating.

According to at least one embodiment of the present disclosure, ultrasound imaging can be used with the navigation system to provide updated imaging of the one or more anatomical elements, which can provide updated information about a pose of the one or more anatomical elements. The pose includes a position and an orientation. The updated images may also be aligned with the preoperative image. Thus, integration of ultrasound and navigation can provide real-time updated imaging of one or more anatomical elements to ensure that the navigation system is navigating relative to a current pose of the one or more anatomical elements.

There are also a number of advantages that combining ultrasound imaging with surgical navigation can offer. Ultrasound does not emit harmful radiation and thus, can be used continuously during a surgical procedure without exposing a patient and a surgical team to radiation. This results in a safer environment for the patient, surgeon, and surgical team. Ultrasound may also be helpful to track certain objects and/or anatomical elements (e.g., soft tissue) as compared to, for example, X-ray based imaging, which may be better suited for other objects/anatomical elements (e.g., hard tissue, manmade objects, etc.). Ultrasound with navigation can be used for multiple applications such as, for example, cranial and/or spinal procedures. Current imaging and navigation can overlay an ultrasound image over a pre-operative image (e.g., an MRI or CT image); take measurements on ultrasound images; and/or capture a series of images and play through the images.

In at least one embodiment, ultrasound navigation may be used for, for example, three-dimensional ultrasound navigation; electromagnetic navigated ultrasound; augment reality; using artificial intelligence to merge ultrasound with pre-operative imaging for real-time brain shift compensation; reconstructing patient anatomy of interest (e.g., vascular and/or tumor); patient auto-registration; tumor ablation confirmation; tracking hardening of biologics; track size of tool (e.g., a balloon) between anatomical elements (e.g., vertebrae); and/or segmental tracking.

Embodiments of the present disclosure provide technical solutions to one or more of the problems of (1) providing a three-dimensional representation of one or more anatomical elements; (2) updating a three-dimensional representation of one or more anatomical elements during a surgical procedure; (3) providing real-time updates of a pose, size, or shape of one or more anatomical elements to a navigation system; (4) providing navigation using three-dimensional representation of one or more anatomical elements; and (5) increasing patient safety.

Turning first toFIG.1, a block diagram of a system100according to at least one embodiment of the present disclosure is shown. The system100may be used to generate a three-dimensional representation or multiple three-dimensional representations of one or more anatomical elements, which may be used for robot navigation during a surgical procedure, and/or carry out one or more other aspects of one or more of the methods disclosed herein. The system100comprises a computing device102, one or more imaging devices112, a robot114, a navigation system118, a database130, and/or a cloud or other network134. Systems according to other embodiments of the present disclosure may comprise more or fewer components than the system100. For example, the system100may not include the imaging device112, the robot114, the navigation system118, one or more components of the computing device102, the database130, and/or the cloud134.

The computing device102comprises a processor104, a memory106, a communication interface108, and a user interface110. Computing devices according to other embodiments of the present disclosure may comprise more or fewer components than the computing device102.

The processor104of the computing device102may be any processor described herein or any similar processor. The processor104may be configured to execute instructions stored in the memory106, which instructions may cause the processor104to carry out one or more computing steps utilizing or based on data received from the imaging device112, the robot114, the navigation system118, the database130, and/or the cloud134.

The memory106may be or comprise RAM, DRAM, SDRAM, other solid-state memory, any memory described herein, or any other tangible, non-transitory memory for storing computer-readable data and/or instructions. The memory106may store information or data useful for completing, for example, any step of the methods300,400,500described herein, or of any other methods. The memory106may store, for example, one or more algorithms120, one or more surgical plans122, and/or one or more reconstruction models124. Such algorithms may, in some embodiments, be organized into one or more applications, modules, packages, layers, or engines. Alternatively or additionally, the memory106may store other types of data (e.g., machine learning models, artificial neural networks, etc.) that can be processed by the processor104to carry out the various method and features described herein. Thus, although various components of memory106are described as algorithms, it should be appreciated that functionality described herein can be achieved through use of instructions, algorithms, and/or machine learning models. The data, algorithms, and/or instructions may cause the processor104to manipulate data stored in the memory106and/or received from or via the imaging device112, the robot114, the database130, and/or the cloud134. The reconstruction models124may be trained (as described with respect toFIG.2), then made available to the computer device102to enable generating three-dimensional representations of one or more objects, anatomical elements, tools, and/or instruments.

The computing device102may also comprise a communication interface108. The communication interface108may be used for receiving image data or other information from an external source (such as the imaging device112, the robot114, the navigation system118, the database130, the cloud134, and/or any other system or component not part of the system100), and/or for transmitting instructions, images, or other information to an external system or device (e.g., another computing device102, the imaging device112, the robot114, the navigation system118, the database130, the cloud134, and/or any other system or component not part of the system100). The communication interface108may comprise one or more wired interfaces (e.g., a USB port, an Ethernet port, a Firewire port) and/or one or more wireless transceivers or interfaces (configured, for example, to transmit and/or receive information via one or more wireless communication protocols such as 802.11a/b/g/n, Bluetooth, NFC, ZigBee, and so forth). In some embodiments, the communication interface108may be useful for enabling the device102to communicate with one or more other processors104or computing devices102, whether to reduce the time needed to accomplish a computing-intensive task or for any other reason.

The computing device102may also comprise one or more user interfaces110. The user interface110may be or comprise a keyboard, mouse, trackball, monitor, television, screen, touchscreen, and/or any other device for receiving information from a user and/or for providing information to a user. The user interface110may be used, for example, to receive a user selection or other user input regarding any step of any method described herein. Notwithstanding the foregoing, any required input for any step of any method described herein may be generated automatically by the system100(e.g., by the processor104or another component of the system100) or received by the system100from a source external to the system100. In some embodiments, the user interface110may be useful to allow a surgeon or other user to modify instructions to be executed by the processor104according to one or more embodiments of the present disclosure, and/or to modify or adjust a setting of other information displayed on the user interface110or corresponding thereto.

Although the user interface110is shown as part of the computing device102, in some embodiments, the computing device102may utilize a user interface110that is housed separately from one or more remaining components of the computing device102. In some embodiments, the user interface110may be located proximate one or more other components of the computing device102, while in other embodiments, the user interface110may be located remotely from one or more other components of the computer device102.

The imaging device112may be operable to image anatomical feature(s) (e.g., a bone, veins, tissue, etc.) and/or other aspects of patient anatomy to yield image data (e.g., image data depicting or corresponding to a bone, veins, tissue, etc.). “Image data” as used herein refers to the data generated or captured by an imaging device112, including in a machine-readable form, a graphical/visual form, and in any other form. In various examples, the image data may comprise data corresponding to an anatomical feature of a patient, or to a portion thereof. The image data may be or comprise a preoperative image, an intraoperative image, a postoperative image, or an image taken independently of any surgical procedure. The imaging device112may be capable of capturing a two-dimensional image, a series of two-dimensional images, a three-dimensional image, and/or a series of three-dimensional images to yield the image data. The imaging device112may be or comprise, for example, an ultrasound scanner (which may comprise, for example, a physically separate transducer and receiver, or a single ultrasound transceiver), an O-arm, a C-arm, a G-arm, or any other device utilizing X-ray-based imaging (e.g., a fluoroscope, a CT scanner, or other X-ray machine), a magnetic resonance imaging (MRI) scanner, an optical coherence tomography (OCT) scanner, an endoscope, a microscope, an optical camera, a thermographic camera (e.g., an infrared camera), a radar system (which may comprise, for example, a transmitter, a receiver, a processor, and one or more antennae), or any other imaging device112suitable for obtaining images of an anatomical feature of a patient.

In some embodiments, the imaging device112may comprise more than one imaging device112. For example, a first imaging device may provide first image data and/or a first image at a first time, and a second imaging device may provide second image data and/or a second image at the first time or at a second time after the first time. In still other embodiments, the same imaging device may be used to provide both the first image data and the second image data, and/or any other image data described herein. The imaging device112may be operable to generate a stream of image data. For example, the imaging device112may be configured to operate with an open shutter, or with a shutter that continuously alternates between open and shut so as to capture successive images. For purposes of the present disclosure, unless specified otherwise, image data may be considered to be continuous and/or provided as an image data stream if the image data represents two or more frames per second.

In some embodiments, the imaging device112may comprise a source and a detector. In such embodiments, the imaging device112may be an ultrasound device or an x-ray imaging device. In some embodiments, the source and the detector may be in separate housings or are otherwise physically separated. In such embodiments, the source may be oriented by a first robotic arm and the detector may be oriented by a second robotic arm, as will be described in more detail below. In other embodiments, the source and the detector may be in the same housing. The source may be configured to emit a wave and the detector may be configured to receive a signal indicative of the emitted wave. The detector may also be configured to save a plurality of image datasets to, for example, the memory106.

In some embodiments, the imaging device112may be a first imaging device112and the system100may include a second imaging device138, which may be the same as or similar to the imaging device112. The second imaging device138may be in communication with the database130. The second imaging device138may provide preoperative images, which may be stored in the database130for use at a later time. For example, a preoperative image of a patient may be obtained at a date prior to a surgical procedure. The preoperative image may be stored in the database130(whether as part of the surgical plan122or separately) and retrieved anytime thereafter. In other instances, the second imaging device138may provide a preoperative image prior to a start of a surgical procedure. The second imaging device138in some embodiments may use a different modality than the first imaging device112. For example, the second imaging device138may be a CT or MRI scanner and the first imaging device112may be an ultrasound device.

The robot114may be any surgical robot or surgical robotic system. The robot114may be or comprise, for example, the Mazor X™ Stealth Edition robotic guidance system. The robot114may be configured to position the imaging device112at one or more precise position(s) and orientation(s), and/or to return the imaging device112to the same position(s) and orientation(s) at a later point in time. The robot114may additionally or alternatively be configured to manipulate a surgical tool (whether based on guidance from the navigation system118or not) to accomplish or to assist with a surgical task. In some embodiments, the robot114may be configured to hold and/or manipulate an anatomical element during or in connection with a surgical procedure.

The robot114may comprise one or more robotic arms116. The robotic arms may be controlled in a single, shared coordinate space, or in separate coordinate spaces. In some embodiments, the robotic arm116may comprise a first robotic arm and a second robotic arm, though the robot114may comprise more than two robotic arms. In some embodiments, one or more of the robotic arms116may be used to hold and/or maneuver the imaging device112. In embodiments where the imaging device112comprises two or more physically separate components such as, for example, the source and the detector, one robotic arm116may hold the source, and another robotic arm116may hold the detector. Each robotic arm116may be accurately positionable independently of the other robotic arm (e.g., the detector can be positioned or oriented independently of the source). In some embodiments, one robotic arm116may orient the source at a first pose across from the detector oriented by another robotic arm116at a second pose. In some embodiments, the source may remain at the same pose while the detector is oriented at different poses. In other embodiments, the detector may remain at the same pose while the source is oriented at different poses. In still other embodiments, both the detector and the source may each be oriented at different poses.

The robot114, together with the robotic arm116, may have, for example, one, two, three, four, five, six, seven, or more degrees of freedom. Further, the robotic arm116may be positioned or positionable in any pose, plane, and/or focal point. As a result, an imaging device112, surgical tool, or other object held by the robot114(or, more specifically, by the robotic arm116) may be precisely positionable in one or more needed and specific positions and orientations.

The robotic arm(s)116may comprise one or more sensors that enable the processor104(or a processor of the robot114) to determine a precise pose in space of the robotic arm (as well as any object or element held by or secured to the robotic arm). Each sensor132may be any kind of sensor132for measuring the pose in space of the robotic arm116. The sensor132may comprise one or more or any combination of components that are electrical, mechanical, electro-mechanical, magnetic, electromagnetic, or the like. The sensor132may comprise, but is not limited to, one or more of a linear encoder, a rotary encoder, a capacitor, and/or an accelerometer. In some embodiments, the sensor132may include a memory for storing sensor data. In still other examples, the sensor132may output signals (e.g., sensor data) to one or more sources (e.g., the computing device102, the navigation system118, and/or the robot114).

The sensor132may be integrated internally into the robotic arm116or otherwise positioned inside of the robotic arm. In some embodiments, the sensor132is positioned inside a joint of the robotic arm116. The sensor132may include a plurality of sensors and each sensor may be positioned at the same location or a different location as any other sensor. For example, a sensor132may be positioned in one or more joints of the robotic arm116. It will be appreciated that in some embodiments the sensor132can be positioned at or on any component of the system100or environment (e.g., on any portion of the navigation system118, the robot114, the robotic arm116, and/or any other component at the surgical site).

The sensor132may be operable to sense and/or monitor the pose (e.g., position and orientation), position, or orientation of any portion of the robotic arm116. The sensor132may send the data to the computing device102at any time, whether continuously, at a time interval, in response to an input from a user requesting the data, or a change in pose, position, or orientation of the robotic arm116. Further, in some embodiments, the sensor132may send data to the computing device102to display on the user interface110.

In some embodiments, reference markers (i.e., navigation markers) may be placed on the robot114(including, e.g., on the robotic arm116), the imaging device112, or any other object in the surgical space. The reference markers may be tracked by the navigation system118, and the results of the tracking may be used by the robot114and/or by an operator of the system100or any component thereof. In some embodiments, the navigation system118can be used to track other components of the system (e.g., imaging device112) and the system can operate without the use of the robot114(e.g., with the surgeon manually manipulating the imaging device112and/or one or more surgical tools, based on information and/or instructions generated by the navigation system118, for example).

In some embodiments, electromagnetic sensor(s) may be used to track any component of the system100including, for example, the imaging device112. The electromagnetic sensor(s) may be used by the navigation system118to track a corresponding component. For example, an electromagnetic sensor may be disposed on or integrated with an ultrasound transducer for tracking a pose of the transducer in real-time. In some embodiments, the electromagnetic sensor may be removable.

The navigation system118may provide navigation for a surgeon and/or a surgical robot during an operation. The navigation system118may be any now-known or future-developed navigation system, including, for example, the Medtronic StealthStation™ S8 surgical navigation system or any successor thereof. The navigation system118may include one or more cameras or other sensor(s) for tracking one or more reference markers, navigated trackers, or other objects within the operating room or other room in which some or all of the system100is located. The one or more cameras may be optical cameras, infrared cameras, or other cameras. In various embodiments, the navigation system118may be used to track a position and orientation (i.e., pose) of the imaging device112, the robot114and/or robotic arm116, and/or one or more surgical tools (or, more particularly, to track a pose of a navigated tracker or an electromagnetic sensor attached, directly or indirectly, in fixed relation to the one or more of the foregoing). The navigation system118may include a display for displaying one or more images from an external source (e.g., the computing device102, imaging device112, or other source) or for displaying an image and/or video stream from the one or more cameras or other sensors of the navigation system118. In some embodiments, the system100can operate without the use of the navigation system118. The navigation system118may be configured to provide guidance to a surgeon or other user of the system100or a component thereof, to the robot114, or to any other element of the system100regarding, for example, a pose of one or more anatomical elements, whether or not a tool is in the proper trajectory, and/or how to move a tool into the proper trajectory to carry out a surgical task according to a preoperative or other surgical plan.

In some embodiments, an ultrasound device136may be integrated with the navigation system118in which images from the ultrasound device may be used by the navigation system118for navigation. In some embodiments, the hardware for an ultrasound device136may be directly integrated with the navigation system118hardware. In other embodiments, the ultrasound device136may be a separate component. Whether directly integrated or combined as separate components, a processor such as the processor104or a processor128of the navigation system118may receive data from the ultrasound device136and automatically process such data for use by the navigation system118.

In embodiments using an integrated navigation system118and ultrasound device136, the navigation system118may navigate a surgeon or robotic system relative to a preoperative image (e.g., MRI or CT image(s)) depicting one or more anatomical elements, and an ultrasound probe may provide real-time or live imaging of the one or more anatomical elements during a surgical procedure. The preoperative image(s) may be obtained from, for example, the database130and/or the second imaging device138. The real-time or live image(s) obtained from the ultrasound device136can be aligned with preoperative image(s) (e.g., MRI or CT images) to confirm or—in instances where an anatomical element has moved—update a pose of the anatomical element and surrounding anatomical elements. The navigation system118may then provide navigation based on the updated pose of the anatomical element(s). Thus, the ultrasound device136enables the navigation system118to continue to navigate when one or more anatomical elements shift or move, either in space or relative to one another. In some instances, the real-time or live image(s) can be used to generate a three-dimensional ultrasound representation that can be overlaid onto a preoperative three-dimensional representation generated from preoperative image(s). The navigation system118may then navigate based on the three-dimensional ultrasound representation. In some instances, the real-time or live image(s) can be used to generate a three-dimensional ultrasound representation that can be overlaid onto a preoperative two-dimensional image that depicts the anatomical elements.

The combined navigation system118and ultrasound device136may be used in various applications. For example, the combined navigation system118and ultrasound device136may be used to view a progress of or confirm a tumor ablation, while the tumor is in the process of being ablated. In such examples, a navigated ultrasound probe may be used to obtain a current ultrasound image of an ablated tumor area, which may be compared to a preoperative image obtained prior to the ablation procedure. In another example, the combined navigation system118and ultrasound device136may be used to auto-register and/or reregister a patient. In such examples, images obtained from the ultrasound device136may be automatically aligned and correlated to preoperative images. In still another example, the combined navigation system118and ultrasound device136may be used generate a three-dimensional representation of one or more anatomical elements based on a set of images and corresponding pose information that can be used by the navigation system118for navigation, as will be described in detail inFIGS.3-5.

The database130may store, for example, the one or more algorithms120, the one or more surgical plans122(including, for example, preoperative image(s); steps for orienting the imaging device112at one or more poses; etc.); one or more images useful in connection with a surgery to be completed by or with the assistance of one or more other components of the system100(e.g., preoperative images from the second imaging device138); and/or any other useful information. The database130may be configured to provide any such information to the computing device102or to any other device of the system100or external to the system100, whether directly or via the cloud134. In some embodiments, the database130may be or comprise part of a hospital image storage system, such as a picture archiving and communication system (PACS), a health information system (HIS), and/or another system for collecting, storing, managing, and/or transmitting electronic medical records including image data.

The cloud134may be or represent the Internet or any other wide area network. The computing device102may be connected to the cloud134via the communication interface108, using a wired connection, a wireless connection, or both. In some embodiments, the computing device102may communicate with the database130and/or an external device (e.g., a computing device) via the cloud134.

The system100or similar systems may be used, for example, to carry out one or more aspects of any of the model architecture200and/or methods300,400,500described herein. The system100or similar systems may also be used for other purposes.

Turning toFIG.2, an example of a model architecture200that supports methods and systems (e.g., Artificial Intelligence (AI)-based methods and/or system) for generating a three-dimensional representation of one or more anatomical elements is shown. It will be appreciated that a three-dimensional representation may be generated for one or more objects, instruments, and/or tools.

A set of images202may be obtained by an imaging device such as the imaging device112. In some embodiments the imaging device may be an ultrasound device. The set of images202may depict one or more objects and/or one or more anatomical elements of, for example, a patient. The set of images202may be obtained at any time such as, for example, preoperatively, intraoperatively, or postoperatively.

Pose information204corresponding to the set of images202may be obtained. The pose information204may be, for example, separate from the set of images and may comprise coordinates of the imaging device when a corresponding image is obtained. The pose information204may be useful for determining a spatial relationship between the set of images202. In some embodiments, the pose information204may be obtained from a navigation system such as the navigation system118which may be configured to track the imaging device112. The imaging device112may be tracked using, for example, reference markers or electromagnetic trackers. In other embodiments, the imaging device112may be supported by a robotic arm such as the robotic arm116and pose information may be obtained from sensors such as the sensors132integrated with or disposed on the robotic arm116. The sensors132may be configured to track, among other things, a pose of the robotic arm116. More specifically, a pose of an end of the robotic arm116may be tracked, or may be determined from a pose of any portion of the robotic arm116. The pose of the robotic arm116may correlate to a pose of the imaging device112when the imaging device112is oriented by the robotic arm116.

The set of images202and the pose information204are received as input by the reconstruction model206,124which may be the same as or similar to the reconstructions model124stored in the memory106. The reconstruction model206may be trained using historical image(s) and/or historical pose information. In other embodiments, the reconstruction model206may be trained using the set of images202and/or the pose information204. In such embodiments, the reconstruction model206may be trained prior to inputting the images202and the pose information204into the reconstruction model206or may be trained in parallel with inputting the set of images202and the pose information204. Training in parallel may, in some embodiments, comprise training a reconstruction model206using the set of images202and the pose information204while also using a separate reconstruction model206to generate the three-dimensional representation208using the set of images202and the pose information204. In some instances, when the reconstruction model206being trained exceeds the reconstruction model206in use (whether in efficiency, accuracy, or otherwise), the reconstruction model206being trained may replace the reconstruction model206in use. Such parallel training may be useful, for example, in situations, where the reconstruction model206is continuously in use (for example, when the at least one image is continuously updated) and a corresponding reconstruction model206may be trained in parallel for further improvements.

The reconstruction model206may be configured to generate a three-dimensional representation208of the one or more anatomical elements. Generating the three-dimensional representation208may include determining a surface representation or virtual boundary of the one or more anatomical elements depicted in the set of images202based on the corresponding pose information. More specifically, in some embodiments, each image may be positioned adjacent to another image based on the respective corresponding pose information and a surface representation may be formed based the relative position of surfaces depicted in each image. In some embodiments, the surface representation may be a virtual mesh. The virtual mesh may comprise, for example, a set of polygonal faces that, when taken together, form a surface covering of a virtual object. The set of polygonal faces may be connected at their edges and vertices to define a shape of the virtual object.

Turning toFIG.3, a method300that may be used, for example, for generating a model is provided.

The method300(and/or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s)104of the computing device102described above. The at least one processor may be part of a robot (such as a robot114) or part of a navigation system (such as a navigation system118). A processor other than any processor described herein may also be used to execute the method210. The at least one processor may perform the method210by executing instructions stored in a memory such as the memory106. The instructions may correspond to one or more steps of the method210described below. The instructions may cause the processor to execute one or more algorithms, such as the algorithm120.

The method300comprises generating a model (step304). The model may be the reconstruction model206,124. A processor such as the processor104,128may generate the model. The model may be generated to facilitate and enable, for example, generating of a three-dimensional representation of one or more anatomical elements and/or objects.

The method300also comprises training the model (step308). In embodiments where the model is trained prior to a surgical procedure, the model may be trained using historical data from a number of patients. In some embodiments, the historical data may be obtained from patients that have similar patient data to a patient on which a surgical procedure is to be performed. In other embodiments, the historical data may be obtained from any patient.

In other embodiments, the model may be trained in parallel with use of another model. Training in parallel may, in some embodiments, comprise training a model using input received during, for example, or prior to a surgical procedure, while also using a separate model to receive and act upon the same input. Such input may be specific to a patient undergoing the surgical procedure. In some instances, when the model being trained exceeds the model in use (whether in efficiency, accuracy, or otherwise), the model being trained may replace the model in use. Such parallel training may be useful, for example, in situations, where a model is continuously in use (for example, when an input (such as, for example, an image) is continuously updated) and a corresponding model may be trained in parallel for further improvements.

In some embodiments, it will be appreciated that the model trained using historical data may be initially used as a primary model at a start of a surgical procedure. A training model may also be trained in parallel with the primary model using patient-specific input until the training model is sufficiently trained. The primary model may then be replaced by the training model.

The method300also comprises storing the model (step312). The model may be stored in memory such as the memory106for later use. In some embodiments, the model is stored in the memory when the model is sufficiently trained. The model may be sufficiently trained when the model produces an output that meets a predetermined threshold, which may be determined by, for example, a user, or may be automatically determined by a processor such as the processor104,128.

The present disclosure encompasses embodiments of the method300that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

FIG.4depicts a method400that may be used, for example, for generating a three-dimensional representation of one or more anatomical elements.

The method400(and/or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s)104of the computing device102described above. The at least one processor may be part of a robot (such as a robot114) or part of a navigation system (such as a navigation system118). A processor other than any processor described herein may also be used to execute the method400. The at least one processor may perform the method400by executing instructions stored in a memory such as the memory106. The instructions may correspond to one or more steps of the method400described below. The instructions may cause the processor to execute one or more algorithms, such as the algorithm120.

The method400comprises receiving a preoperative image (step404). The preoperative image may be obtained from an imaging device such as the second imaging device138and/or a database such as the database130. In some embodiments, the second imaging device is a CT scanner or an MRI scanner. The preoperative image may comprise one or more two-dimensional images, one or more three-dimensional images, or a combination of one or more two-dimensional images and one or more three-dimensional images. In some embodiments, the preoperative image may be obtained from a surgical plan such as the surgical plan122. In other embodiments, the preoperative image may be received via a user interface such as the user interface110and/or via a communication interface such as the communication interface108of a computing device such as the computing device102, and may be stored in a memory such as the memory106. The image data may also be generated by and/or uploaded to any other component of the system100. In some embodiments, the preoperative image may be indirectly received via any other component of the system100or a node of a network to which the system100is connected.

The preoperative image may depict one or more anatomical elements. In some embodiments, the preoperative image may contain hard tissue information about the one or more anatomical elements. In other embodiments, the preoperative image may contain soft tissue information about the one or more anatomical elements.

The method400also comprises orienting an imaging device at one or more poses (step408). The imaging device may be the same as or similar to the imaging device112or an ultrasound device such as the ultrasound device136. In some embodiments, the ultrasound device is integrated with a navigation system such as the navigation system118. In some embodiments, the imaging device may be oriented by a robotic arm such as the robotic arm116at the one or more poses. In other embodiments, the imaging device may be oriented by a user at the one or more poses.

The one or more poses may be obtained from, for example, a surgical plan such as the surgical plan122. In other embodiments, the one or more poses may be received via a user interface such as the user interface110and/or via a communication interface such as the communication interface108of a computing device such as the computing device102, and may be stored in a memory such as the memory106. In still other embodiments, the one or more poses may be automatically determined by a processor such as the processor104,128. In such embodiments, a user such as a surgeon or other medical provider may select one or more anatomical elements to image and the processor may determine the one or more poses to obtain images of the one or more anatomical elements.

The method400also comprises receiving an image at each of the one or more poses to form a set of images (step412). The set of images may be the same as or similar to the set of images202. Each image of the set of images may be, in some instances, a two-dimensional image. The set of images may depict one or more anatomical elements. The one or more anatomical elements depicted in the set of images may be the same as the one or more anatomical elements depicted in the preoperative image. In other instances, the set of images may depict at least one of the one or more anatomical elements depicted in the preoperative image.

It will be appreciated that each image of the set of images may depict the one or more anatomical elements from different angles or viewpoints as defined by each pose of the one or more poses. In some instances, some of the images of the set of images may depict one anatomical element and other images of the set of images may depict another anatomical element. In other instances, the set of images may depict the same anatomical element(s).

The method400also comprises receiving pose information (step416). The pose information may be pose information for each pose of the one or more poses (which correspond to each image of the set of images). As previously described, the pose refers to a position and an orientation. The pose information may be, for example, coordinates of the imaging device when a corresponding image is obtained. In some embodiments, the pose information may be obtained from a navigation system such as the navigation system118. In such embodiments, the imaging device may include a reference marker or an electromagnetic tracker tracked by the navigation system. In other embodiments, the pose information may be obtained from a robotic arm such as the robotic arm116when the imaging device is oriented by the robotic arm. In such embodiments, the robotic arm may comprise a sensor such as the sensor142configured to provide pose data of the robotic arm. The sensor may provide pose data of an end of the robotic arm (e.g., a pose of the imaging device disposed at the end of the robotic arm) or may provide pose data of any portion of the robotic arm. In the latter instances, a pose of the imaging device can be determined from the pose data based on a distance between the portion of the robotic arm and the imaging device.

It will be appreciated that in some embodiments, the pose information may only contain information about a position or an orientation of the imaging device.

The method400also comprises inputting the set of images and the pose information to a reconstruction model (step420). The reconstruction model may be the same as or similar to the reconstruction model206,124. The reconstruction model may be configured to generate a three-dimensional representation of the one or more anatomical elements based on the set of images and the pose information. In some embodiments, the preoperative image and corresponding preoperative pose information may also be inputted into the reconstruction model. In at least some embodiments, the reconstruction model may generate the three-dimensional representation of the one or more anatomical elements based on the set of images, the pose information, the preoperative image, and the preoperative pose information. In other instances, the reconstruction model may output a separate three-dimensional representation of one or more anatomical elements depicted in the preoperative image. In such instances, the three-dimensional representation of the one or more anatomical elements depicted in the set of images may be overlaid or compared to the three-dimensional representation of the one or more anatomical elements depicted in the preoperative image. For example, the three-dimensional representation of the one or more anatomical elements depicted in the set of images may be formed from ultrasound images, which may be overlaid onto the three-dimensional representation of the one or more anatomical elements depicted in the preoperative image, which may be formed from X-ray images. Thus, in such examples, soft tissue information (as obtained from the ultrasound images) and hard tissue information (as obtained from the X-ray images) may both be provided for the one or more anatomical elements.

The reconstruction model may be trained using historical sets of image(s) and/or historical pose information. In some embodiments, the historical sets of image(s) may depict one or more anatomical elements similar to the one or more anatomical elements depicted by the preoperative image. In other embodiments, the historical sets of image(s) may depict one or more anatomical elements different from the one or more anatomical elements depicted by the preoperative image.

Generating the three-dimensional representation may include determining a surface representation or virtual boundary of the one or more anatomical elements depicted in the set of images (and, in some cases, the preoperative image) based on the corresponding pose information (and, in some cases, the preoperative pose information). More specifically, in some embodiments, each image may be positioned adjacent to another image based on the respective corresponding pose information and a surface representation may be formed based the relative position of surfaces depicted in each image.

The method400also comprises receiving, from the reconstruction model, a three-dimensional representation of one or more anatomical elements (step424). As described above, the three-dimensional representation of the one or more anatomical elements may comprise a surface representation of the one or more anatomical elements. In some embodiments, the surface representation may be a virtual mesh. The three-dimensional representation may also comprise pose information of the one or more anatomical elements. In some embodiments, the three-dimensional representation may comprise hard tissue and/or soft tissue information. Further, the three-dimensional representation may be measured to provide information about a size, volume, dimensions, or shape of the one or more anatomical elements.

The method400also comprises generating instructions for navigating based on the three-dimensional representation of the one or more anatomical elements (step428). A navigation system such as the navigation system118may provide the navigation. The instructions may be generated for navigating one or more instruments, tools, and/or anatomical elements, by a user such as a surgeon or other medical provide or by a robotic arm such as the robotic arm116. The instructions may be generated by a processor such as the processor104,128(whether of the navigation system or as a separate component). The instructions may be machine readable data and transmitted to, for example, the robotic arm to cause the robotic arm to execute the instructions. The instructions may also be human readable data and may be displayed on a user interface such as the user interface110for instructing the user.

The method400also comprises segmenting at least one of the one or more anatomical elements from the three-dimensional representation (step442). Segmenting at least one of the one or more anatomical elements from the three-dimensional representation of the one or more anatomical elements may comprise identifying a boundary of the at least one anatomical element and forming a separate three-dimensional representation of the at least one anatomical element. In some embodiments, identifying the boundary may comprise identifying adjacent sets of pixels having a large enough contrast to represent a border of an anatomical element depicted therein. In other embodiments, feature recognition may be used to identify a border of an anatomical element. For example, a contour of a vertebrae may be identified using feature recognition. The three-dimensional representation of the at least one anatomical element may be separately tracked and/or updated.

The present disclosure encompasses embodiments of the method400that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

FIG.5depicts a method500that may be used, for example, for generating an updated three-dimensional representation of one or more anatomical elements.

The method500(and/or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s)104of the computing device102described above. The at least one processor may be part of a robot (such as a robot114) or part of a navigation system (such as a navigation system118). A processor other than any processor described herein may also be used to execute the method500. The at least one processor may perform the method500by executing instructions stored in a memory such as the memory106. The instructions may correspond to one or more steps of the method500described below. The instructions may cause the processor to execute one or more algorithms, such as the algorithm120.

The method500comprises receiving at least one updated image (step504). The step504may be the same or similar to the step408of method400described above. The at least one updated image may be received from the same imaging device as the set of images. In other instances, the at least one updated image may be received from a different imaging device as the set of images. The at least one updated image may depict one or more anatomical elements, which may be the same as or similar to the one or more anatomical elements depicted in the set of images. In some embodiments, the at least one updated image may be obtained from at least one of the one or more poses. In other embodiments, the at least one updated image may be obtained from one or more updated poses.

The at least one updated image may be obtained automatically. For example, the imaging device may continuously obtain images subsequent to the set of images. In another example, the imaging device may obtain images at a time interval. In other embodiments, the at least one updated image may be obtained when a user such as a surgeon or other medical provider inputs instructions for the imaging device to obtain the at least one updated image. In such embodiments, the user may, for example, wish to confirm a pose of an anatomical element, or may be aware of a shift or change to an anatomical element and may wish to update the three-dimensional representation with such new information.

In embodiments where a pose, position, orientation, size, or shape of an anatomical element is to be confirmed, the at least one updated image may be compared to corresponding image(s) of the set of images. In such embodiments, the at least one updated image may be obtained from at least one of the one or more poses. Comparing the at least one updated image and the corresponding image(s) of the set of images may comprise aligning the at least one updated image and the corresponding image(s) of the set of images and detecting any changes between the images. In such embodiments, the at least one updated image and the corresponding image(s) of the set of images may be obtained from the imaging device at the same pose. In other embodiments, at least one updated image and the corresponding image(s) of the set of images may be obtained from different poses. In such embodiments, the one or more anatomical elements depicted in the at least one update image may be aligned with the one or more anatomical elements depicted in corresponding image(s) of the set of images and changes may be detected between one or more anatomical elements depicted in the images.

The method500also comprises receiving updated pose information (step508). The step508may be the same as or similar to the step412of the method400described above.

The method500also comprises inputting the at least one updated image and the updated pose information to a reconstruction model (step512). The step512may be the same as or similar to the step420of the method400described above. The reconstruction model may be the same as or similar to the reconstruction model206,125. In some embodiments, generating the updated three-dimensional representation may comprise replacing at least one image of the one or more images with the at least one updated image.

For example, where a change in the one or more anatomical elements is detected such as in, for example, step504, at least one image of the one or more set of images may be replaced with the at least one updated image. In other embodiments, at least one image of the one or more set of images may be replaced with the at least one updated image regardless of whether a change is detected. In still other embodiments, when a change is not detected, the at least one image of the one or more set of images may not be replaced with the at least one updated image. In such embodiments, the at least one updated image may be saved to, for example, a memory such as the memory106, or discarded.

The method500also comprises receiving, from the reconstruction model, an updated three-dimensional representation of the one or more anatomical elements (step516). The step516may be the same as or similar to the step420of the method400described above. The updated three-dimensional representation may include new information about a pose, size, shape, position, or orientation of the one or more anatomical elements.

It will be appreciated that in some embodiments, the steps505,508, and/or512may be continuously repeated to provide updates regarding a pose, position, orientation, size, or shape of the one or more anatomical elements. In other words, at least one updated image may be obtained continuously, and in some instances, the subsequent updated image(s) may be inputted into the reconstruction model to continuously generate an updated three-dimensional representation of the one or more anatomical elements.

The present disclosure encompasses embodiments of the method500that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

It will be appreciated that any of the steps of methods300,400, and/or500may be combined in any order. For example, some steps of method400and some steps of method500may be combined and executed. As noted above, the present disclosure encompasses methods with fewer than all of the steps identified inFIGS.3-5(and the corresponding description of the methods300,400,500), as well as methods that include additional steps beyond those identified inFIGS.3-5(and the corresponding description of the methods300,400,500). The present disclosure also encompasses methods that comprise one or more steps from one method described herein, and one or more steps from another method described herein. Any correlation described herein may be or comprise a registration or any other correlation.

The foregoing is not intended to limit the disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the disclosure are grouped together in one or more aspects, embodiments, and/or configurations for the purpose of streamlining the disclosure. The features of the aspects, embodiments, and/or configurations of the disclosure may be combined in alternate aspects, embodiments, and/or configurations other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, embodiment, and/or configuration. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate preferred embodiment of the disclosure.

Moreover, though the foregoing has included description of one or more aspects, embodiments, and/or configurations and certain variations and modifications, other variations, combinations, and modifications are within the scope of the disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, embodiments, and/or configurations to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.