Method and apparatus for hybrid cone beam computed tomography and intraoral scan image modeling

Abstract

Methods and apparatus for generating a hybrid (e.g., fused) cone beam computed tomography (CBCT) scan using intraoral scan data. Methods and apparatus for more efficiently processing CBCT data are also described herein. Also described herein are methods and apparatus for enhancing dental and / or orthodontic treatment planning using hybrid CBCT and intraoral scan data, methods and apparatus for interactively presenting hybrid CBCT and intraoral scans and generating one or more treatment plans in conjunction with a user and / or a dental instrument for treating a patient according to a treatment plan that takes into account hybrid CBCT and intraoral scans.

Description

[0001] Cross-references to related applications

[0002] This patent application claims priority to U.S. Provisional Patent Application No. 63 / 499,478, filed May 1, 2023, entitled “METHODS AND APPARATUSES FOR HYBRID CONE BEAMCOMPUTED TOMOGRAPHIC AND INTRAORAL SCAN IMAGE MODELING,” the entire contents of which are incorporated herein by reference. Background Technology

[0003] Intraoral scanning is increasingly becoming the standard practice in dentistry, especially for orthodontic treatment planning. Unfortunately, most intraoral scanners only allow visualization of the crowns and gingiva. The roots and surrounding bone (e.g., alveolar bone) are typically not visible and therefore cannot be directly considered when performing treatment planning. Once treatment planning begins, this can lead to problems such as root collisions, fenestrations, and unplanned and unpredictable tooth movements.

[0004] While X-ray imaging such as cone-beam computed tomography (CBCT) may be available, CBCT scans have proven difficult to integrate into most treatment planning processes, particularly for orthodontic treatment planning, including the use of appliances (e.g., shell appliances). This may be partly due to differences in resolution and scan quality between CBCT and intraoral scans, as well as the relative complexity of manipulating CBCT data and the resulting data structure.

[0005] What is needed are methods and devices (including software) that can integrate CBCT scans into proven techniques such as intraoral scanning to better model patients’ dentition and improve patient treatment outcomes. Summary of the Invention

[0006] This document describes methods and apparatus for generating hybrid (e.g., fused) cone-beam computed tomography (CBCT) scans using intraoral scan data. Methods and apparatus for processing CBCT data more efficiently are also described herein. Methods and apparatus for enhancing dental and / oral treatment planning using hybrid CBCT and intraoral scan data are further described herein. Specifically, methods and apparatus for interactively presenting hybrid CBCT and intraoral scans and combining them with users such as physicians, dentists, and technicians to generate one or more treatment plans and / or dental instruments for treating patients based on treatment plans that take into account hybrid CBCT and intraoral scans are described herein.

[0007] The methods and devices described herein for generating hybrid CBCT and intraoral scans overcome the difficulties that have traditionally hindered the adoption and use of CBCT scans in treatment planning and execution. These methods and devices offer specific improvements over existing technologies and systems that are slow, difficult to implement, and less suitable for generating treatment plans and designing dental instruments that need to conform to and apply force to the patient's teeth with a certain degree of precision.

[0008] For example, the methods and apparatus described herein can provide automatic (or semi-automatic) segmentation of CBCT data and fusion with intraoral scans. The resulting 3D digital model, including the fused CBCT data and intraoral scan data, can be interactively used to develop treatment plans that take into account the geometry of the actual tooth roots (e.g., the long axis direction) and allow interactive visualization of the tooth roots and their motion in the treatment plan, including dynamically displaying the predicted positions and orientations of the tooth roots, bones (e.g., alveolar bone), gingiva, etc., including predictions of problems such as collisions and fenestrations.

[0009] For example, this paper describes methods for forming hybrid (e.g., fusion) digital models of a patient's dentition (e.g., maxilla and / or mandible, crowns, roots, gingiva, bone, etc.). These methods and devices (e.g., apparatus and systems, particularly including software, hardware, and / or firmware) offer specific improvements over existing technologies and systems that attempt to use CBCT scans and / or scans for orthodontic treatment planning. Such systems and technologies are often too long to upload and process, and may not allow combination with other scan types (such as intraoral scans) or digital modeling based on other scan types, as the quality of CBCT scans may be insufficient or incompatible with other scan types and / or models based on these other scan types. In some of the methods and devices described herein, these problems can be overcome by local preprocessing of the CBCT scans by a local processing agent before transmitting them for combination with intraoral scan (or other scan types) data. In the context of CBCT scans, "local" can refer to being local to the user (e.g., dentist, physician, orthodontist, technician, etc.) and / or can refer to the site storing and / or recording the CBCT scans being local. CBCT scans can be fused with intraoral scans at a remote site by a remote processing agent that is separate from the local processing agent. This allows for rapid and immediate feedback to the user, including expedited processing (providing quick feedback) and rejection of scans that are unlikely to be effective early in the process.

[0010] For example, this paper describes a method for fusing cone-beam computed tomography (CBCT) scans with intraoral scans. This method may include: receiving, in a remote processing agent, a processed CBCT scan file that has already been processed by a local processing agent through the following steps: limiting the file size of the patient's CBCT scan file to less than a maximum file size and pre-segmenting it by the remote processing agent to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented; fusing the CBCT scan from the processed CBCT scan file with an intraoral scan of the patient's tooth crown to form a final model of the patient's tooth including the tooth roots, wherein the processed CBCT scan has been volumetrically segmented and the intraoral scan has been surface-segmented.

[0011] For example, this paper describes a method for fusing cone-beam computed tomography (CBCT) scans with intraoral scans, the method comprising: receiving, in a remote processing agent, a processed CBCT scan file that has been processed by a local processing agent through the following steps: limiting the file size of the patient's CBCT scan file to less than a maximum file size by truncating the file to remove one or more regions outside any tooth root, and performing pre-segmentation to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented; segmenting the processed CBCT scan file in the remote processing agent; and fusing the segmented CBCT scans with segmented intraoral scans of the patient's tooth crowns to form a final model of the patient's tooth including the tooth roots.

[0012] Receiving processed CBCT scan files may include receiving processed CBCT scan files that have been processed to limit their file size to less than a maximum file size. This limitation is achieved by truncating the patient's CBCT scan file (e.g., the "raw" CBCT scan file) to remove one or more areas outside the region containing the tooth root. The maximum file size may be predetermined or set, including adjustments based on connection speed. For example, the maximum file size may be 10 GB or less (e.g., 7.5 GB or less, 6 GB or less, 5 GB or less, 4 GB or less, 3 GB or less, 2 GB or less, etc.). A local processing agent may prevent the first user (e.g., an orthodontist requesting treatment planning) from transmitting the CBCT scan file before its size is reduced. Generally, the CBCT scan files described herein can be in any suitable format, including (but not limited to) Medical Digital Imaging and Communications (DICOM) files.

[0013] In some examples, receiving processed CBCT scan files may include receiving processed CBCT scan files that have been processed to limit the file size to less than a maximum file size, by truncating the patient's CBCT scan file to remove one or more layers of the patient's CBCT scan file to limit the file size to less than the maximum file size. For example, in cases where the scan covers a large vertical area outside the teeth, DICOM files (".dcm" files) may be processed to manually or automatically remove one or more layers from the top and / or bottom of the scan. Similarly, a local processing agent may adjust other dimensions of the scan to remove areas that do not include the teeth (crowns and roots and / or bone areas adjacent to the roots within a few millimeters).

[0014] Receiving processed CBCT scan files may include receiving processed CBCT scan files that have been pre-segmented based on scan quality to reject blurry and / or below a minimum resolution threshold CBCT scan files that cannot be segmented based on scan quality. Scan quality can typically include any indicators of visual quality and / or scan integrity. For example, a local agent may apply one or more thresholds for scan quality, including thresholds for blurriness, motion artifacts, brightness (e.g., dynamic optical range), resolution, etc. The local agent may determine the integrity of the CBCT scan, including confirming the presence of the entire maxilla and / or mandible, the full extent of all teeth or a subset of teeth (roots, crowns, etc.), bones, etc. The local processing agent may receive scan quality parameters from a remote processing agent. The local processing agent may also confirm that only a single CBCT scan exists.

[0015] A local processing agent typically determines whether a CBCT scan file can be adequately segmented for fusion with a second scan type (e.g., an intraoral scan). For example, as described above, the local processing agent can determine this based on scan quality and scan integrity. In some examples, the local processing agent can apply a trained neural network to determine whether a CBCT scan file can be segmented, wherein the trained neural network is trained on a database of CBCT scans with different scan qualities.

[0016] In many of the examples described herein, segmentation can be performed by a remote processing agent. However, in some examples, CBCT scan segmentation can be performed by a local processing agent, and fully segmented or partially segmented CBCT scans can be transmitted from the local processing agent to the remote processing agent as processed CBCT scans. For example, receiving a processed CBCT scan file by the remote processing agent may include receiving a processed CBCT scan file that has already been segmented in volume by the local processing agent.

[0017] In any of these methods and apparatuses, CBCT scan files (e.g., processed scan files) can be segmented in volume. For example, these methods may include segmenting a received processed CBCT scan file in volume.

[0018] The second scan to be fused with the CBCT scan can also be segmented. For example, an intraoral scan can be segmented. In some examples, the method may include segmenting the intraoral scan, for example, via a remote processing agent. The CBCT scan and the second scan (e.g., the intraoral scan) can be segmented differently; for example, the CBCT scan may be segmented volumetrically, while the intraoral scan may be segmented surface-wise.

[0019] In some examples, processed, segmented CBCT scans can be fused with intraoral scans. Fusion may include matching the crown regions of the segmented intraoral scans with the crown regions of the segmented CBCT scans, and replacing the crown regions of the segmented CBCT scans with the crown regions of the segmented intraoral scanners. In some examples, fusion may include modifying the crown regions of the segmented intraoral scans based on the crown regions of the segmented CBCT scans, and using the modified crown regions. In some examples, fusion may include identifying which portion of the segmented CBCT scan matches the segmented intraoral scan. The crown regions of the intraoral and / or CBCT scans may be scaled and / or moved (e.g., rotated) relative to each other for alignment and matching. In some examples, as part of the fusion process, the segmented crown regions of the intraoral scans and / or individual teeth or subsets of teeth from the CBCT scans may be manipulated relative to each other. For example, the crown region of a single tooth from the intraoral scan may be manipulated individually for matching and fusion with the CBCT scan. The size of the crown region in a CBCT scan can be matched with the size of the crown in an intraoral scan.

[0020] In any of these examples, fusion may be validated based on the degree of matching between the crown regions of segmented intraoral scans and segmented CBCT scans. For example, the methods and apparatus described herein may apply a threshold to confirm that the fusion is sufficient based on the degree of matching.

[0021] Therefore, the final model of the patient's teeth obtained can include the root and crown of each tooth, with the CBCT scan improved by intraoral scanning of the crown. The final model can include, or can be used to generate, the long axis of each tooth determined from the root axis of each tooth in the CBCT scan. The obtained long axis can be used for treatment planning and / or prediction of movement, collisions, fenestrations, etc.

[0022] Any of these methods and devices (e.g., systems) may include a user interface. The user interface can be particularly effective by including a final model of the patient's teeth from a fused (hybrid) CBCT / intraoral scan. For example, any of these methods may include displaying the final model of the patient's teeth in a user interface configured to allow the user to interactively display subsets of segmented regions of the final model. For example, allowing the user to interactively display subsets of segmented regions may include receiving user commands to show one or more of the following: unerupted teeth, roots only, surrounding translucent bone, and crowns only. The user can interactively change multiple portions of the final model of the patient's teeth to display all or some segments (regions). A fused CBCT crown obtained from an intraoral scan can provide a very high-fidelity representation of the crown(s) surface(s), while the CBCT roots and other segmented regions (e.g., bone) can provide a larger background.

[0023] Any of the methods described herein, including those fusing cone-beam computed tomography (CBCT) scans and intraoral scans, can be performed by a device including a system, apparatus, etc., containing software. For example, a non-transitory computing device-readable medium having instructions stored thereon is described herein, which can be executed to perform any of these methods. For example, a method as described herein may include a non-transitory computing device-readable medium having instructions stored thereon, which can be executed by a processor of a remote processing agent to cause the remote processing agent to perform a method comprising the following steps: receiving a processed CBCT scan file that has been processed by a local processing agent through the following steps: limiting the file size of the patient's CBCT scan file to less than a maximum file size and pre-segmenting it by the remote processing agent to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented; fusing the CBCT scan from the processed CBCT scan file with an intraoral scan of the crown of the patient's tooth to form a final model of the patient's tooth including the tooth roots, wherein the processed CBCT scan has been volumetrically segmented and the intraoral scan has been surface segmented.

[0024] For example, a non-transitory computing device readable medium having instructions stored thereon can enable a remote processing agent to execute a method, the instructions of which can be executed by the processor of the remote processing agent, the method comprising: receiving, in the remote processing agent, a processed CBCT scan file that has been processed by a local processing agent through the following steps: limiting the file size of the patient CBCT scan file to less than a maximum file size by truncating the file to remove one or more regions outside any tooth root, and performing pre-segmentation to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented; segmenting the processed CBCT scan file in the remote processing agent; and fusing the segmented CBCT scan with intraoral scans of segmented crowns of the patient's teeth to form a final model of the patient's teeth including the tooth roots.

[0025] This document also describes methods and apparatus that can be performed by a local processing agent. For example, a method for processing cone-beam computed tomography (CBCT) scans may include: accessing a patient's CBCT scan file using a local software processing agent; limiting the file size of the CBCT scan file to less than a maximum file size; pre-segmenting the CBT scan by a remote processing agent to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented; and uploading the processed CBCT scan file to a remote site for fusion with intraoral scans from the patient.

[0026] Any of these methods can be combined in whole or in part (for example, these methods may include methods performed by both local processing agents and remote processing agents).

[0027] As described above, limiting the file size of a CBCT scan file to less than the maximum file size may include truncating the CBCT scan file to remove one or more areas outside the region containing the tooth root. In some examples, limiting the file size includes truncating the patient's CBCT scan file to remove one or more layers of the patient's CBCT scan file.

[0028] Pre-segmentation of CBCT scan files based on scan quality can include rejecting blurry and / or below a minimum resolution threshold CBCT scan files that cannot be segmented based on scan quality. For example, pre-segmentation of CBCT scan files based on scan quality involves applying a trained neural network to determine whether a CBCT scan file can be segmented, wherein the neural network is trained on a database of CBCT scans with different scan qualities.

[0029] Any of these methods may include, for example, segmenting the processed CBCT scan file by volume by a local processing agent before transmitting the processed CBCT scan. Alternatively, the processed CBCT scan file may be segmented by a remote processing agent. As mentioned above, the CBCT scan file can be any suitable file type, including Medical Digital Imaging and Communications (DICOM) files.

[0030] Any of the methods and devices described herein may include displaying one or more messages to a user regarding the scan quality of a CBCT scan file before uploading the processed CBCT scan file.

[0031] For example, a method for processing cone-beam computed tomography (CBCT) scans may include: accessing a patient's CBCT scan file using a local software processing agent; limiting the file size of the CBCT scan file to less than a maximum file size by truncating the CBCT scan file to remove one or more regions outside the region containing the tooth root; pre-segmenting the CBCT scan by a remote processing agent to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented, wherein the scan quality includes one or more of the following: blurriness and resolution; and uploading the processed CBCT scan file to a remote site for fusion with intraoral scans from the patient.

[0032] This document also describes one or more local processing agents, which may be part of a system that includes a remote processing agent. The local processing agent can perform any of the methods described herein for preprocessing CBCT scans. For example, a local processing agent for processing cone-beam computed tomography (CBCT) scans may include a non-transitory computing device-readable medium on which instructions are stored, which can be executed by the processor of a remote processing agent to cause the remote processing agent to perform a method comprising: accessing a patient's CBCT scan file using the local software processing agent; limiting the file size of the CBCT scan file to less than a maximum file size; pre-segmenting the CBCT scan by the remote processing agent to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented; and uploading the processed CBCT scan file to a remote site for fusion with an intraoral scan from the patient.

[0033] In some examples, a local processing agent for processing cone-beam computed tomography (CBCT) scans may include a non-transitory computing device-readable medium storing instructions executable by a processor of a remote processing agent to cause the remote processing agent to perform a method comprising the following steps: accessing a patient's CBCT scan file using the local software processing agent; removing one or more regions outside the area containing the tooth root by truncating the CBCT scan file, limiting the file size of the CBCT scan file to less than a maximum file size; pre-segmenting the CBCT scan by the remote processing agent to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented, wherein the scan quality includes one or more of the following: blurriness and resolution; and uploading the processed CBCT scan file to a remote site for fusion with an intraoral scan from the patient.

[0034] Typically, fused CBCT scans and intraoral scans (e.g., a final model of a patient's tooth including segmented roots) can be used for treatment planning, and particularly for interactive treatment planning, to allow users to display and manipulate digital representations of the patient's teeth, thereby predicting tooth movement and potential defects, such as windowing, more quickly and accurately, which can be generated by one or more suggested movements as part of the treatment plan. Therefore, methods and devices for interactively displaying and predicting tooth movement and potential defects in tooth movement, particularly those involving interaction with surrounding bone (e.g., alveolar bone) and gingiva, are also described herein. The methods and devices described herein represent a significant and particular improvement over prior art systems because these methods (and the systems used to perform them) can predict windowing and allow users to adjust tooth movement within the treatment plan and view changes in the predicted windowing in response to changes in the treatment plan. This can be done in real time. This improvement is possible in part due to the use of segmented fused CBCT scans and intraoral scans including roots and bone (from CBCT scans) and crowns (from intraoral scans), as well as the characteristics of the user interface.

[0035] For example, this paper describes methods and devices for predicting and visualizing potential windowings resulting from one or more stages of a proposed treatment plan; these methods and devices can be configured to allow a user to interactively modify the treatment plan to adjust the proposed plan and to view the effects on relationships between teeth, between teeth and alveolar bone, and / or gingiva. Any of these methods and devices can be used specifically for predicting windowings.

[0036] The method may include receiving a digital three-dimensional (3D) model of a patient's teeth, wherein the 3D model of the patient's teeth includes a fusion of a CBCT scan of the patient's jaw and an intraoral scan of the patient's crown region of the patient's teeth; using the 3D model of the patient's teeth, simulating the movement of the tooth root relative to the patient's alveolar bone for one or more steps of a treatment plan for orthodontic movement of the patient's teeth; identifying the formation of one or more openings of the tooth root from the simulation for one or more steps of the treatment plan; and displaying the 3D model of the patient's teeth for one or more steps of the treatment plan, the model showing the identified one or more openings.

[0037] Any of these methods may include receiving one or more modifications to the treatment plan from the user; and simulating the movement of the tooth root relative to the patient's alveolar bone, and displaying a 3D model of the patient's tooth with one or more windows identified as modifications.

[0038] The method may include receiving a command from a user to display a window. For example, receiving a command may include interactively switching between stages of treatment planning based on user input and displaying a 3D model of the patient's teeth showing one or more identified windows.

[0039] User input can be received via a user interface that may include one or more images displaying the patient’s teeth, including optionally displaying one or more of the following: crown, root, gingiva, alveolar bone.

[0040] Any of these methods may include identifying the formation of one or more cracks in the tooth root from a simulation of one or more steps of treatment planning, and displaying a 3D model of the patient's tooth for one or more steps of treatment planning, showing the identified one or more cracks. Alternatively or additionally, any of these methods may include identifying the formation of one or more projections of the tooth root relative to the alveolar bone (e.g., into the sinus cavity) in a simulation of one or more steps of treatment planning, and displaying a 3D model of the patient's tooth for one or more steps of treatment planning, showing the identified one or more projections. The simulation may include determining the long axis of each tooth using the long axis of the root portion of each tooth from the 3D model, and modeling the motion of the tooth root based on the forces applied to the crown of the tooth and the relative positions of adjacent teeth including the root portions of adjacent teeth.

[0041] For example, a method may include: receiving a digital three-dimensional (3D) model of a patient's tooth, wherein the 3D model of the patient's tooth includes a fusion of a CBCT scan of the patient's jaw and an intraoral scan of the patient's crown region of the patient's tooth; using the 3D model of the patient's tooth, simulating the movement of the tooth root relative to the patient's alveolar bone for one or more steps of a treatment plan for orthodontic movement of the patient's tooth; identifying the formation of one or more windows of the tooth root from the simulation for one or more steps of the treatment plan; receiving a command from a user to display the windows; displaying the 3D model of the patient's tooth for one or more steps of the treatment plan, the 3D model showing the identified one or more windows; receiving one or more modifications to the treatment plan from the user; and correcting the simulation of the movement of the tooth root relative to the patient's alveolar bone, and displaying the corrected 3D model of the patient's tooth showing the identified one or more windows.

[0042] In some examples, the method may include: receiving a digital three-dimensional (3D) model of a patient's teeth, wherein the 3D model of the patient's teeth includes a fusion of a CBCT scan of the patient's jaw and an intraoral scan of the patient's crown region of the patient's teeth; using the 3D model of the patient's teeth, simulating the movement of the tooth roots relative to the patient's alveolar bone for one or more steps of a treatment plan for orthodontic movement of the patient's teeth; identifying the formation of one or more alveolar bone defects, said one or more alveolar bone defects including one or more of the following: fenestration of the tooth root from the simulated one or more steps of the treatment plan, cracking of the tooth root from the simulated one or more steps of the treatment plan, and one or more protrusions of the tooth root from the alveolar bone from the simulated one or more steps of the treatment plan, and displaying the 3D model of the patient's teeth for the one or more steps of the treatment plan, the 3D model showing the identified one or more protrusions; and displaying the 3D model of the patient's teeth for the one or more steps of the treatment plan, which shows the identified one or more alveolar bone defects.

[0043] Therefore, the methods and apparatus described herein can predict the occurrence of one or more of the following: fenestrations, protrusions, and dehiscences that may occur in treatment planning. Fenestrations, protrusions, and dehiscences can be accurately predicted using the fusion CBCT / intraoral scan digital model described above. In some cases, the prediction of fenestrations, protrusions, and dehiscences can be performed automatically for one or more stages of the proposed treatment plan. In some cases, the method and / or apparatus can automatically predict the probability of one or more of fenestrations, protrusions, and dehiscences in the proposed treatment plan for one or more stages using the fusion CBCT / intraoral scan digital model, and if the probability of fenestrations, protrusions, and / or dehiscences exceeds a threshold (e.g., a threshold for fenestrations, a threshold for protrusions, a threshold for dehiscences), the method and / or apparatus can highlight and / or display the possible fenestrations, protrusions, and / or dehiscences. Therefore, in any of these methods and devices, when planning orthodontic treatment, users (e.g., doctors, dentists, orthodontists, etc.) can benefit from the integration of intraoral scan data on the crowns with extended CBCT data, particularly as the system can rapidly and efficiently generate fused and segmented digital scans of the patient's oral cavity, including both CBCT and intraoral scan data. The resulting fused CBCT / intraoral scan data can be integrated into treatment planning as 3D surface data of the tooth roots and external surface data of the bone. This data can be used to detect potential problems caused by the proposed treatment or variations thereof, including protrusions from one or more teeth into the sinuses and protrusions from the teeth into the jawbone. These methods and devices can highlight areas of the tooth, root, or bone surfaces susceptible to fenestration, protrusions, and / or cracking, and often highlight features that may lead to unpredictable tooth movements. Incorporating these methods and devices into the treatment planning process, and particularly allowing visualization of the crowns, roots, and alveolar bone, can help avoid potential problems and significantly reduce the risk of unpredictable tooth movements, including root impaction and fenestration.

[0044] Typically, these methods can be used to automatically segment and fuse CBCT data with intraoral scans, as well as to construct treatment plans that take into account the actual root geometry, including long axis orientation.

[0045] As described above, these methods and devices may include a user interface that allows a user to visualize real tooth roots and their movements in treatment planning with various options, including displaying only teeth with their actual (real) roots (obtained from CBCT scan data), displaying teeth with their actual (real) roots with translucent bone, displaying teeth with their actual (real) roots with opaque bone, displaying one or more reference static bones: portions of the maxilla, mandible, and adjacent bones, and visualizing root collisions and possible virtual root openings.

[0046] The user interface can be configured to allow users to view and interact with the resulting 3D model of the patient's maxilla and / or mandible in a manner similar to that of a traditional DICOM data file (e.g., after a CBCT scan). These methods and devices can be configured to allow users to visualize unerupted, supernumerary, and affected teeth in treatment planning, including selectively showing or hiding one or more of these teeth. These methods and devices can enhance the ability of treatment planning to achieve root parallelism as part of the treatment planning process. Any of these methods and devices can be used to plan dental implants in place of or supplement treatment planning for orthodontic alignment.

[0047] All methods and apparatuses described herein, in any combination, are considered herein and can be used to achieve the benefits described herein. Attached Figure Description

[0048] The features and advantages of the methods and apparatus described herein will be better understood by referring to the detailed implementation of the illustrative embodiments and the accompanying drawings, in which:

[0049] Figures 1A to 1C This illustration schematically demonstrates a method for local preprocessing of CBCT scans in preparation for fusion with intraoral scans. Figure 1A A method for fusing processed CBCT scans with intraoral scans ( Figure 1B Examples of methods for dynamically identifying one or more defects in a treatment plan and / or modifying the treatment plan using fusion scanning.

[0050] Figure 2 An example of an overview of the methods using CBCT scans and intraoral scans as described in this article is shown.

[0051] Figure 3 An example of a system for fusing CBCT scans and intraoral scans, as described herein, is illustrated.

[0052] Figure 4 This illustration schematically demonstrates a method for preprocessing CBCT scans in preparation for fusion with intraoral scans.

[0053] Figure 5 An example of a user interface for interactively displaying a patient's final digital model of teeth is shown, which includes fused CBCT scans and intraoral scans.

[0054] Figure 6An example of the user interface is shown, illustrating predicted root collisions in treatment planning using a digital model of the patient's teeth, including fused CBCT scans and intraoral scans.

[0055] Figure 7A and Figure 7B An example of the user interface is shown, illustrating the use of a digital model of a patient's teeth, including a fused CBCT scan and an intraoral scan, to detect unerupted teeth.

[0056] Figure 8A Examples of openings, protrusions, and cracks are illustrated.

[0057] Figure 8B An example of the user interface is shown, which illustrates an interactive examination with a windowed view of a digital model of a patient's teeth, including fused CBCT scans and intraoral scans, during the proposed treatment plan.

[0058] Figure 8C An example of the user interface is shown, which illustrates an interactive examination with a windowed view of a digital model of a patient's teeth, including fused CBCT scans and intraoral scans, during the proposed treatment plan.

[0059] Figure 9A and Figure 9B An example of a user interface is shown, which is configured to interactively display features detected using a digital model of a patient's teeth, including fused CBCT scans and intraoral scans.

[0060] Figure 10A and Figure 10B An example of a user interface is shown for displaying a digital model of a patient's teeth, including fused CBCT scans and intraoral scans.

[0061] Figure 11 The illustration shows an example of a method for using a digital model of a patient's teeth, including fused CBCT scans and intraoral scans, for treatment planning.

[0062] Figure 12 A diagram illustrating an example of a computing environment that includes the CBCT scan fusion module described herein is shown. Detailed Implementation

[0063] This document describes methods and devices (e.g., apparatuses, systems, etc., including software, firmware, and hardware) for identifying and visualizing problems, particularly those caused by tooth movement during preparation for treatment of a patient's teeth as part of a proposed treatment plan. These methods can advantageously include dynamically predicting and / or identifying such problems during the proposed treatment plan and allowing the user (e.g., physician, dentist, orthodontist, etc.) to modify the proposed treatment plan and examine the impact of any modifications on these problems. These methods and devices for performing them can be executed in real time. The treatment plan may be a plan for moving (e.g., aligning) patient teeth, removing teeth, adding dental implants, etc.

[0064] Problems that can be identified and visualized using the methods and devices described herein include, but are not limited to, fenestrations, protrusions into sinus cavities (“protrusions”), and fissures. Visualization of potential problems in any of these methods and devices significantly reduces the risk of unpredictable tooth movements. Unpredictable tooth movements can occur when calculated tooth movements (e.g., due to fenestrations of the tooth in the bone tissue at any stage of treatment) do not occur. Currently, there is no reliable and rapid way to predict whether bone tissue will grow at a specific rate or whether such movement will occur when a tooth moves into a part of the bone. Protrusions into sinuses can cause upper respiratory problems, so it is important to attempt to prevent such movements when planning treatment. The methods and devices described herein can utilize an improved fused digital model of the patient’s dentition, which advantageously includes, for example, high-resolution information about the two crowns from intraoral scans of the patient’s teeth, as well as cone-beam computed tomography (CBCT) data about the roots and jawbone. In particular, the methods and apparatus described herein include techniques for generating fused digital models of a patient’s dentition that avoid long-standing problems in dealing with file size (especially CBCT scans) and compatibility between CBCT and intraoral scans.

[0065] Methods and devices can detect fenestrations, protrusions, and fissures as part of an interactive user interface. Fissures can be detected and visualized early in treatment planning. For visualization, these methods and devices can divide bone eruption into two parts: legal and illegal, and can mark illegal eruptions in the maxilla and mandible, which may fill the portion of the tooth root protruding from the jawbone near the crown. Fenestrations can be detected by identifying the region of the tooth and / or the jaw geometry beneath the crown. Protrusions can be predicted by determining a plane at the level of the tooth root and identifying the jawbone region protruding from the bone tissue. The methods and devices described herein can preprocess CBCT scans automatically (or semi-automatically, e.g., using prescribed feedback from the user) and fuse the preprocessed CBCT scans with intraoral scans. CBCT scans can be preprocessed (including local preprocessing, e.g., local to the user) to ensure compatibility with the fusion of intraoral scans and to allow the fusion process to be performed at a remote site (e.g., via a processor different from the user's local processor(s)). The fusion of CBCT and intraoral scans can include matching segmented crowns from CBCT scans with intraoral scans in 3D space. Once the crowns are matched, the root surfaces from the CBCT data can be stitched to the crown surfaces from the intraoral data for each tooth to generate a fused digital model. This fused digital model can be used for treatment planning, and the user can visually see the actual tooth roots as part of the treatment plan. The methods and apparatus described herein can include workflows for a multimodal treatment planning process in which the fused digital model (including both CBCT and intraoral scan data) is performed.

[0066] Figures 1A to 1C Together, examples are shown of methods for generating a fused digital 3D model of a patient's dentition and for interactively predicting the presence and location of problems such as fenestrations, protrusions, and / or cracks. This fused digital 3D model incorporates both CBCT data and intraoral scan data, the problems arising from treatment planning tailored to the patient's teeth. Furthermore, Figure 1A , Figure 1B and Figure 1C Each of these describes separately the following methods: a method for preprocessing CBCT scans for transmission and fusion, a method for fusing preprocessed CBCT scans with intraoral scans of the patient's teeth, and a method for interactively modifying the proposed treatment plan based on predicted problems.

[0067] For example, Figure 1AAn example of a method for preprocessing a patient's CBCT scan in preparation for fusing it with a second scan, such as an intraoral scan, is shown. As used herein, the intraoral scan can be a surface scan, for example, using white light or other frequencies (e.g., fluorescence, discrete visible light frequencies, infrared, etc.). In particular, these methods can be used to fuse digital models of the patient's tooth surfaces obtained using an intraoral scanner, which can have relatively high resolution. Figure 1A The method shown can be used to preprocess one or more CBCT scans and can be performed independently or as part of a workflow for generating and / or modifying patient treatment plans.

[0068] exist Figure 1A In this system, a user can first refer to a patient's CBCT scan, for example, as part of a request to generate a digital model of the patient's dentition, and / or as part of a request to generate or modify a treatment plan. Optionally, a user can request to perform a CBCT scan or may perform a CBCT scan. Subsequently, the CBCT scan can be accessed as a CBCT scan file. 101 The CBCT scan can be accessed from a first (e.g., local) processor using a first (e.g., local) processing agent. The first processing agent can be local to the user. The CBCT scan can be accessed from a library of patient CBCT scans and can be associated with the patient. In some cases, multiple patient CBCT scans can be accessed, and one or more of them can be selected or chosen. For example, if multiple CBCT scans are available for the same patient, the user can select one, or the local software processing agent can automatically select one (e.g., if a particular CBCT scan is rejected, it can be marked in or by the local software processing agent, and another patient CBCT scan can be selected until an appropriate (or "best") CBCT scan is selected).

[0069] Subsequently, the patient's CBCT scan is preprocessed by a local software processing agent 103. As used herein, the local software processing agent can be a software agent, such as a program running on a local processor (e.g., a computer, smartphone, tablet, etc.), or it can be locally accessible but distributed across a remote processor (e.g., a component or cloud component including one or more web access). Preprocessing of the CBCT scan can be performed to standardize the size of the CBCT scan, including eliminating CBCT scan files that are too large or too small (e.g., in one example, greater than 3 gigabytes and less than 6 megabytes). The local software processing agent can resize the file, including removing one or more layers and / or removing (or simplifying) areas outside the skeletal (e.g., tooth roots, crowns, and jaw) regions. For example, the local software processing agent can automatically or manually remove one or more layers of CBCT scan from a CBCT scan file, and / or can identify one or more missing layers. In some cases, CBCT scan files that are too small (e.g., less than 6 MB) may be incomplete scans.

[0070] In any of these methods and devices, the local software processing agent can determine the dimensions of the scanned jaw as part of a preprocessing step and can confirm that the jaw height is greater than a minimum threshold (e.g., 50 mm). For example, the local software processing agent can assume that scans with heights less than this minimum threshold will not include all root apexes and may therefore be incomplete. Alternatively or additionally, any local software processing agent described herein can confirm that the slice thickness value (which may be, for example, in metadata associated with the CBCT scan file) is equal to and / or less than a minimum slice thickness attribute value (e.g., 0.8, 0.7, 0.6, 0.5, 0.3, 0.15, etc.). The slice thickness attribute is an example of a parameter indicating the resolution of a CBCT scan.

[0071] In some examples, the local software processing agent can examine the patient's CBCT scan file to confirm that the number of slices is correct. For example, this method can determine whether multiple slices (more than one) of the scan are missing or damaged. In some examples, the local software processing agent can determine whether the missing slices include bone or teeth (e.g., crowns, roots, etc.), which could affect the necessary digital model data.

[0072] Alternatively or additionally, the local software processing agent can verify that the user has selected the correct CBCT scan file(s) when submitting the case. For example, the local software processing agent can verify that the CBCT scan has the correct digital compatibility dimension (DCM) and / or correct any identification errors. The local software processing agent can also, or alternatively, verify that only a single CBCT scan file has been submitted, as in some cases a user may submit multiple scans for the same patient. In any of these methods and devices, the local software processing agent can identify non-CBCT files (and prevent their transfer).

[0073] In some examples, the local software processing agent can examine the quality of CBCT scans within a CBCT scan file and can accordingly reject and / or adjust the CBCT scan file. For example, the methods and apparatus described herein can determine the resolution of a CBCT scan file and determine that the resolution is within an acceptable range (e.g., above a certain minimum resolution).

[0074] Preprocessing CBCT scan files by a local software processing agent is particularly important because it helps prevent problems when transferring CBCT scans to a remote software processing agent for fusion with a second (e.g., intraoral or surface) scan. These problems could lead to treatment planning rejection and / or potentially significant delays in the aforementioned process. Otherwise, such problems could force users to resubmit CBCT cases, causing delays in the patient and treatment planning process, and potentially requiring new appointments and rescans (e.g., for new CBCT scans), resulting in unnecessary additional radiation doses. These problems can be addressed by including, as described herein, […]. Figure 1A Preprocessing step 109 is used to prevent this.

[0075] In any of the methods described herein, a preprocessing step, which can be performed by a local software processing agent, can verify and / or prepare the patient's CBCT scan file for segmentation. This process may be referred to as pre-segmented CBCT scanning. Pre-segmented CBCT scanning can ensure that the output of preprocessing, for example, the processed CBCT scan file, can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan. Preprocessing may also result in the rejection of CBCT scan files that cannot be segmented.

[0076] In some cases, pre-segmentation may involve applying one or more sets of rules to determine whether a CBCT scan file can be segmented. For example, these methods may determine whether a CBCT scan file can be segmented by applying rapid partial segmentation of the CBCT scan file to identify any issues related to segmentation (particularly volumetric segmentation based on scan file size, resolution, and integrity). In some examples, CBCT scans may be segmented as part of a preprocessing step, and the processed CBCT scan file may include segmented scan files. Therefore, in some examples, the processed CBCT scan file may be preprocessed by a local processing agent and fully or partially segmented.

[0077] As described above, preprocessing by the local processing agent may include rejecting and / or modifying CBCT scan files, including examining data and / or metadata within the CBCT scan files. Once the CBCT scan file has been preprocessed and has not been rejected by the local processing agent, the preprocessed CBCT scan file can be uploaded to a remote site as a processed CBCT scan file for fusion with intraoral scans from the patient 107. Therefore, in Figure 1A In the diagram, the output of the method can be a preprocessed CBCT scan file. If the method (or the device performing the method) rejects a CBCT scan file (e.g., due to resolution, ambiguity, size, segmentation capability, etc.), the method or device can repeat the process, for example, by selecting another CBCT scan file and preprocessing that next scan file; the process can be repeated iteratively until a preprocessed scan file that can be fused with an intraoral scan passes through.

[0078] Preprocessing may include using one or more trained machine learning agents to perform all or some of these steps. For example, a trained machine learning agent may be used to determine whether a CBCT scan can be segmented. The machine learning agent may be trained on a dataset that includes CBCT scans that can or cannot be segmented (including indicators that indicate whether a document can or cannot be segmented). In some examples, the device or method may include a trained machine learning agent that is trained to determine whether one or more visual quality parameters (e.g., blur / clarity, resolution, etc.) are sufficient or insufficient.

[0079] Figure 1B An example of a method for fusing pre-processed CBCT scans with a second scan (such as an intraoral scan) is shown. For example, in Figure 1B In this process, the first step includes receiving a preprocessed CBCT scan file 111, which can be preprocessed as described above. In some examples, the method described herein for fusing CBCT scans with intraoral scans 119 may include segmenting the CBCT scan. Figure 1BAny fusion steps shown or described as part of the method may be performed by a remote processing agent separate from the local processing agent. The remote processing agent may receive and store processed CBCT scans that have been approved for fusion with intraoral scans.

[0080] exist Figure 1B In this context, methods for fusing CBCT scans with a second (e.g., intraoral) scan may include receiving and / or storing a digital intraoral scan or a 3D model derived from the intraoral scan. The intraoral scan may be segmented by a remote processing agent or may be segmented separately, including prior to reception. Segmentation of the intraoral scan data may include segmentation of the 3D surfaces of the teeth. Figure 1B In the example, method 119 may include fusing preprocessed and segmented CBCT scans with segmented intraoral scans. For example, CBCT scans from processed CBCT scan files may be fused with intraoral scans of the crowns of a patient's teeth to form a final model of the patient's teeth (including roots). Thus, the final model may include a fusion of processed CBCT scans that have been segmented in volume and intraoral scans that have been surface-segmented 113.

[0081] Fusion may involve matching the surface of the crown region from an intraoral scan with the crown region from a CBCT scan. Prior to matching and fusion, either or both of the processed CBCT scan and intraoral scan may be scaled and / or rotated (by segmented regions or as a whole). Therefore, the resulting fused 3D digital model can be a digital three-dimensional (3D) model of the patient's teeth, comprising a fusion of a CBCT scan of the patient's jaw with an intraoral scan of the patient's crown region of the teeth.

[0082] A fused digital three-dimensional (3D) model of the patient's teeth, including a CBCT scan of the patient's jaw and an intraoral scan of the patient's crown region (e.g., a "fused digital 3D model"), can be used to display one or more features of the digital model, including ectopic and / or unerupted teeth, roots, roots and crowns, or jawbone (e.g., alveolar bone). The fused digital 3D model can be displayed interactively and / or used to design treatment plans that take into account the actual ("real") root shape and axis.

[0083] In some examples, the fused digital 3D model can be used to predict and display one or more of fenestrations, protrusions, and / or fissures in treatment planning. In some examples, the fused digital 3D model can be used to interactively and / or iteratively refine treatment planning. Figure 1C This demonstrates the use of fused digital 3D models (such as those from...) Figure 1B and Figure 1A One method 131 is to receive a fused digital 3D model. Figure 1CIn this method, the fused digital 3D model can be received by a user interface 121. In some examples, the user interface may be part of a local processing agent or the same system as the local processing agent. In some examples, the user interface for displaying and interacting with the fused digital 3D model may be part of a remote user interface that the user can access via a network. In some examples, the user interface is part of or communicates with a remote processing agent. The method may include simulating the movement of the tooth root relative to the patient's alveolar bone using the fused digital 3D model for one or more steps of a treatment plan for orthodontically moving a patient's tooth 123. The movement of the tooth root may be simulated for each stage of the treatment plan. As part of the simulation, the method may include identifying possible windowing and / or protrusions and / or fissures of the tooth root from the simulation of the one or more steps of the treatment plan 125. For example, windowing may be predicted based on the simulated relative movement of the tooth root and surrounding bone. The fused digital 3D model of the patient's tooth may be displayed for the one or more steps of the treatment plan, showing the one or more identified windowings 127.

[0084] In some examples, users can adjust treatment plans based on displayed simulated movements and / or predicted problems (such as fenestration and / or protrusion and / or cracking, one or more of these), including adjusting the proposed movements and / or phases of movement of the teeth, adding / removing attachments, removing tooth materials (reduction), etc.129 The method may then include repeating the steps of simulating and identifying and displaying fenestration and / or protrusion and / or cracking, allowing users to iteratively adjust treatment plans.

[0085] Therefore, integrated digital 3D models can enable various improved methods for patient treatment.

[0086] Figure 2 An overview of the methods for forming fused digital 3D models, as described in this paper, is presented. Figure 2The method may include an optional step whereby a patient scans their teeth using a CBCT scanner 201 and uploads the resulting scans (as DIACOM) files to a data storage device 202. These raw CBCT scan data files may be preprocessed as described above, including confirming that they can be segmented, and, if requested, uploaded to a remote processing agent where they can be segmented 203 (or they may be segmented before transmission). The patient's teeth may be scanned in parallel or at different times 207, and the resulting scans of the patient's teeth may be segmented 209. The remote processing agent may then fuse the segmented CBCT scans with segmented intraoral (surface) scans 204, the segmented CBCT scans being segmented via volumetric segmentation techniques and the intraoral (surface) scans being segmented using surface segmentation techniques. The resulting fused digital 3D model may then be presented to the user 205 as part of a user interface to allow selective visualization of crowns, roots, bones, gingiva, etc.

[0087] Figure 3 An example of a system for performing the methods described herein is shown, including Figure 1A , Figure 1B and Figure 2 The method shown. In Figure 3 In this system, device 300 includes a local processing agent 301, which may include a local user interface 303 or be separate from the local user interface. The local processing agent can be configured to receive and / or access one or more CBCT files 307 (e.g., a library of CBCT files). The local processing agent may include software, hardware, and / or firmware, and can be configured to perform any of the preprocessing steps described above. In some cases, multiple local agents 301(n) and / or local user interfaces 303(n) may be included as part of the system, and each may have access to the stored CBCT files 307. The local processing agent and / or local user interface may also be configured to perform... Figure 1B The remote processing agent 305 communicates (including wirelessly) with any of the steps described herein (including forming a fused digital 3D model). In some cases, the remote processing agent 305 may be configured to perform... Figure 1C Most steps and / or inputs can be output and received from one or more local user interfaces 303, 303(n).

[0088] As described above, the methods described herein may include methods for preprocessing raw CBCT scan data (e.g., locally) such that it can be used by (e.g., remotely) a processing agent to form a fused digital 3D model, and optionally display one or more features of the fused digital 3D model and / or predict deficiencies in treatment planning (such as fenestration). Figure 4 and Figure 1B Similarly, a method for preprocessing CBCT scans to form processed CBCT scans is shown. Figure 4 In this process, the user can first select one or more CBCT scan data files 401. This can be done, for example, in a local processing agent, locally by the user, and may include using a browser (e.g., a web browser) to select between one or more files. Once a file is selected 403, the local processing agent can lock the selection control, for example, to prevent the selection of multiple files 405, and can begin preprocessing the selected CBCT scan file. The local processing agent can display the current status of the processing agent (e.g., “Verify CBCT scan data”) 407 to the user on a user interface (which may be a local user interface or a different user interface). This method may include extracting one or more features of the raw CBCT scan during preprocessing for analysis 411. The extracted features can be derived from the image itself and / or from metadata (header data) in the file. Subsequently, the method or system can perform the aforementioned verification steps, such as (but not limited to) confirming that the CBCT scan data file can be segmented, adjusting layers, resizing the file, confirming that there are no missing layers, etc. 413. In some cases, a trained neural network can be used to determine one or more of these verification steps. Subsequently, any of these methods may include presenting one or more explanations of any errors or problems with the initial / raw CBCT scan data. The system can then determine (e.g., due to any verification step) whether the processed CBCT scan data can be successfully used 415; if so, the obtained preprocessed CBCT scan data file can be uploaded (or allowed to be uploaded), and the scan selection controls can be unlocked 417. If not, the system or method can determine whether the verification was partially successful 419, wherein the method or system can display a warning indication and instruct the user on how to continue 425. Alternatively, the system or method can determine that the verification stage of preprocessing failed, requiring feedback to resolve one or more errors (or granting approval for automatic resolution) 421, and can repeat the process to allow the user to select another file (in the event of failure) or adjust the current CBCT file (if partially successful).

[0089] Figure 5 Figure 10 illustrates an example of the user interface and the use of the fused digital 3D model described herein. For example, Figure 5An example of a user interface is shown that allows the display of different parts (e.g., different segments) of a merged digital 3D model. Figure 5 In the top left, the fused digital 3D model 501 is manipulated by a user interface to receive control information, which displays standard views of the crown 525 and gingiva 529. In this example, the bottom of the user interface includes selectable stage indicators, allowing the user to choose between different stages of treatment planning. In another view 503, the user can choose to display the crown 525 and bone 521 (as shown in the image). Figure 5 (As shown in the upper right). In any of these views, the user can rotate or pan the upper jaw and / or lower jaw. Figure 5 The lower left shows another view of the user interface, 505, which only shows the root 527 and the crown. Finally, Figure 5 The lower right section shows an example of a semi-transparent view including the root 527, crown 525, and bone 521. During operation, the user can switch between any of these views.

[0090] Other examples of user interface options are in Figure 6 As shown in the examples. In any of these examples, the methods described herein can be used to identify collisions of one or more tooth roots during the generation and / or analysis of treatment plans. For example, Figure 6 An example of a collision 623 (highlighted in a magnified area) between a pair of tooth roots 627 during at least one treatment phase is shown. The fused digital 3D model includes a skeletal region 621, a crown region 625, and tooth roots 627. In this example, the user interface can automatically or semi-automatically check the treatment plan while using the fused digital 3D model and can display identified problems, such as collision 623, as shown. In some cases, the user interface may allow the user to toggle between displaying the tooth roots and / or optionally displaying the collision (after a collision has been detected using the fused digital 3D model) and / or displaying other features.

[0091] For example, Figure 7A and Figure 7B This demonstrates the use of a user interface to visualize ectopic and / or unerupted teeth. Figure 7A In the interface, the crown and root of the tooth are displayed, with the bone area around the tooth shown as translucent, revealing a pair of unerupted ectopic teeth that can be repaired (or removed) during treatment. Figure 7B It shows the relationship with Figure 7A The user interface shown has the same view, but the surrounding skeletal area is made completely transparent.

[0092] Typically, these user interfaces can be used in conjunction with fused digital 3D models to display one or more predicted defects, such as... Figure 8A As shown, features include fenestrations 802, fissures 804, and protrusions 806 extending into the sinus region 808. The user interface can also be configured to display these defects against a background of regular teeth 810, roots 812, and / or jawbone 814. Figure 8B An example of a user interface is shown that uses a fused digital 3D model to predict possible windowing, fissures, and / or protrusions from a stage of treatment planning. The user interface may include one or more user-selectable controls to switch between these different display options (e.g., showing one or more predicted windowing, fissures, and / or protrusions, showing the crown region and / or root and / or bone (solid or translucent, etc.)). For example, the user interface may include a "Show Windowing" control input that summarizes a potential virtual windowing of the fused digital 3D model at the selected stage of treatment planning.

[0093] Figure 8C 1 to Figure 8C Image 4 shows a user interface image, which respectively shows an input (e.g., toggle) for displaying an open window and an closed window. Figure 8C 1, Figure 8C 4) and open ( Figure 8C 2, Figure 8C 3) The fused digital 3D model. In Figure 8C 2 and Figure 8C In Figure 3, the front and top views of the fused digital 3D model show possible openings indicated by dark colors.

[0094] Typically, the user interface can display one or more features of the merged digital 3D model, such as Figure 9A and Figure 9B As shown. For example, the user interface can switch between showing or hiding tooth roots, bones (e.g., alveolar bone / jawbone), gingiva, etc. Individual teeth can be displayed and / or manipulated, and individual treatment stages can be displayed. For example, a user can select one or more teeth and move them along the x, y, z axes, or rotate / tilt them using controls on the user interface. These changes to user input regarding treatment planning can modify the treatment plan and allow for recalculation of predicted tooth collisions / root collisions, windowing, etc. These treatment plans are useful for treating extensive malocclusions, including surgery, restorations, expansion / extraction, etc. In any of these examples, in addition to those described above... Figures 5 to 9B The teeth shown in the image ( Figure 10B In addition to CBCT scans, user input may also include, or alternatively, the display of the CBCT scan (see, for example...). Figure 10A ).

[0095] As mentioned above, traditional treatment planning for dental procedures (such as tooth alignment) does not incorporate CBCT scans into the treatment planning process and the generation of one or more (e.g., a series) dental instruments used to perform the treatment plan. Physicians typically perform these procedures without precise information about the tooth roots. When it comes to obtaining information about the root movements typical of a treatment plan, CBCT scan data is required, and physicians cannot plan specifically for the roots because they cannot “see” their movements throughout the treatment. This method and equipment (e.g., software, hardware, firmware, etc.) allows physicians, for the first time, to precisely visualize and plan treatments with the tooth roots in mind.

[0096] Furthermore, these methods and devices can provide treatment planning automatically or semi-automatically through a data fusion process as described herein (e.g., between CBCT scans and intraoral scans). This can be achieved by matching segmented crowns from CBCT scans with intraoral scans in 3D space. Once the crowns are matched, the root surfaces from CBCT data for each tooth and the crown surfaces from intraoral data can be stitched together and visually displayed to the technician / designer and / or clinician in a software user interface. The technician / designer can then conceptualize a treatment plan with the roots. Subsequently, a new treatment plan with accurate, actual data about the roots can be published to a clinician-facing user interface where the clinician can visually see the actual roots in the proposed plan and make modifications / edits.

[0097] Typically, these methods and apparatuses for combining CBCT scan data with intraoral scan data can be implemented as one or more modules, including a CBCT scan fusion engine having one or more modules (e.g., a preprocessing module, a file reduction module, etc.). Any of these apparatuses may include one or more processors for performing the methods described herein. A processor may include hardware that runs computer program code. Specifically, the term "processor" may include a controller and may encompass not only computers with different architectures such as single / multiprocessor architectures and sequential (von Neumann) / parallel architectures, but also special-purpose circuitry such as field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), signal processing devices, and other devices.

[0098] A CBCT fusion engine may include one or more modules (e.g., a patient CBCT scan file input module, a processed CBCT scan file generation module, a processed CBCT scan truncation module, a CBCT scan pre-segmentation module, a CBCT scan file verification module, and an intraoral scan / CBCT scan suturing module) and one or more data storage devices (e.g., an intraoral scan data storage device). In some examples, the CBCT fusion engine includes a local CBCT scan processing engine and a remote CBCT scan processing engine. For example, a local CBCT scan processing engine may include a patient CBCT scan file input module, a processed CBCT scan file generation module, a processed CBCT scan truncation module, a CBCT scan pre-segmentation module, and an optional CBCT scan file verification module. A remote CBCT scan processing engine may include an intraoral scan / CBCT scan suturing module. Alternatively, all these modules (e.g., the entire CBCT fusion engine) may be local or remote.

[0099] The CBCT fusion engine described herein can be executed by one or more processors. As used herein, an engine includes one or more processors or a portion thereof. A portion of one or more processors may include some parts of the hardware, rather than all the hardware of any given one or more processors, such as a subset of registers, a portion of the processor dedicated to one or more threads of a multi-threaded processor, a time slice of the processor wholly or partially dedicated to performing a portion of the engine's functionality, etc. Thus, the first engine and the second engine may have one or more dedicated processors, or the first engine and the second engine may share one or more processors with each other or with other engines. As mentioned above, depending on a particular implementation or other considerations, the engine may be centralized or its functionality may be distributed. An engine may include hardware, firmware, or software embodied in a computer-readable medium for execution by a processor. The processor uses implemented data structures and methods to transform data into new data, as described with reference to the accompanying figures herein.

[0100] The engine described herein, or the engine through which the systems and devices described herein are implemented, can be a cloud-based engine. As used herein, a cloud-based engine is an engine that can use a cloud-based computing system to run applications and / or functions. All or part of the applications and / or functions can be distributed across multiple computing devices and are not required to be limited to only one computing device. In some embodiments, a cloud-based engine can execute functions and / or modules accessible to end users through a web browser or container application without requiring the functions and / or modules to be installed locally on the end user's computing device. In some cases, as described above, it may be particularly advantageous to keep some or all of these engines local rather than cloud-based.

[0101] As used herein, a data storage device is intended to include any repository suitable for organizing data, including tables, character-delimited value (CSV) files, conventional data storage devices (such as SQL), or other applicable known or convenient organizational formats. A data storage device can be implemented, for example, in a physical computer-readable medium on a dedicated machine, in firmware, in hardware, in a combination thereof, or as software embodied in an applicable known or convenient device or system. Components associated with a data storage device, such as data storage device interfaces, can be considered “part” of the data storage device, part of some other system component, or a combination thereof, although the physical location and other characteristics of the components associated with the data storage device are not critical to understanding the techniques described herein.

[0102] Data storage can include data structures. As used herein, a data structure is associated with a specific way of storing and organizing data in a computer, enabling it to be used effectively in a given context. Data structures are typically based on the computer's ability to retrieve and store data at any location in its memory, specified by an address, a bit string that can itself be stored in memory and manipulated by a program. Thus, some data structures are based on using arithmetic operations to compute the address of a data item; others are based on storing the address of the data item within the structure itself. Many data structures use both principles, sometimes combined in a meaningful way. Implementing a data structure typically requires writing a set of programs that create and manipulate the structure. The data storage described herein can be a cloud-based data storage. A cloud-based data storage is a data storage system compatible with cloud-based computing systems and engines.

[0103] The patient CBCT scan file input module can be configured to receive patient CBCT scans, for example, from a CBCT scan data storage device, from a remote location, or as part of a CBCT scanner. The patient CBCT scan file input module can receive patient CBCT scan files and pass them to a processed CBCT scan file generation module. The processed CBCT scan file generation module can construct a processed CBCT scan file (including modified CBCT scans obtained from the received patient CBCT scan files). The processed CBCT scan file generation module can adjust the file size of the processed CBCT scan file as described above. For example, the processed CBCT scan file generation module can truncate portions of the CBCT scan derived from the received patient CBCT scan. This can be performed by a processed CBCT scan truncation module, which can be invoked by the processed CBCT scan file generation module or can be included as part of the processed CBCT scan file generation module, and can reduce the file size as described above, for example, by removing portions of the scan outside the tooth root or other areas. The processed CBCT scan file generation module and / or CBCT scan truncation module may include a trained machine learning agent to perform full or partial truncation and / or other steps for generating the processed CBCT scan file. The processed CBCT scan file generation module may also invoke and / or include a CBCT scan pre-segmentation module that can pre-segment the CBCT scans in the processed CBCT scan file. The CBCT scan fusion engine may also include a CBCT scan file verification module that can verify that the CBCT scans in the processed CBCT scan file and / or the CBCT scans in the patient's CBCT scan file are suitable for use or to verify it as described above. The intraoral scan / CBCT scan suturing module can combine intraoral scans with CBCT scans in the processed CBCT scan file (assuming it has been verified, for example, by the processed CBCT scan file verification module).

[0104] Typically, the methods and apparatus described herein may include forming and / or manufacturing one or more dental instruments from treatment plans generated and / or modified as described herein. As used herein, generating dental instruments may include generating digital models of the one or more dental instruments (e.g., a series of dental instruments), including forming digital files that can be used by a manufacturer to produce physical instruments to be provided to a patient. In some cases, these dental instruments may be manufactured using additive manufacturing (e.g., 3D printing) techniques. Therefore, one or more orthodontic appliance manufacturing engines are described herein that can implement one or more automated agents configured to manufacture dental instruments (e.g., orthodontic appliances).

[0105] The method described in this paper for forming an improved digital model of a patient's dentition using root information from CBCT scans and crown surface information from intraoral scans can be included as part of a workflow for improving dental and medical treatments. For example, Figure 11 An example of a process flow 1100 for using CBCT scans and fusing CBCT scans with intraoral scans of the patient’s teeth for treatment planning as described herein is shown. Figure 11 The first part of the illustrated process (e.g., steps 1101-1110) shows an alternative variation of preprocessing and processing CBCT scans when a user (e.g., a physician) requests a prescribed treatment plan (e.g., for a range of dental appliances). The physician can select CBCT scans and / or generate a request for a treatment plan that includes CBCT scans. The method can preprocess the scans (e.g., retain / reject, modify, confirm characteristics), and then the CBCT scans can be fused with intraoral scans (steps 1111-1115). The resulting fused digital 3D model can then be used to perform the treatment plan (steps 1116-1117).

[0106] For example, a doctor can initially upload a CBCT scan to a data storage device or system to generate a treatment plan (see below for example). Figure 12Uploading can be performed as part of the CBCT scanner or separately, including as part of a user interface, which may be part of a web browser. Before uploading the scan, or as part of the upload process, the system may perform in-browser verification of the CBCT scan 1102. This may include verifying the integrity of the scan and / or scan file. This may include verifying the association with a specific patient, such as linking to existing patient files. This may optionally include formatting or other preprocessing steps for the patient's CBCT scan. In some cases, uploading may include transferring the patient's CBCT scan (e.g., the raw CBCT scan) to a database / data storage 1103. In some cases, the data storage may be local and accessible to the user (e.g., a physician), or the data storage may be remote (e.g., cloud-based, such as part of a commercial web service) 1103; in some cases, the CBCT scan is stored in a secure cloud-based data storage. In some cases, as described above, patient CBCT scans can be preprocessed to generate processed CBCT scan files from patient CBCT scan files that have already been preprocessed as described herein, and in lieu of the "original" patient CBCT scan file, or in addition to the "original" patient CBCT scan file, the processed CBCT scan file 1104 can be stored. For example, as described herein, the size of the CBCT scan obtained from the patient CBCT scan file can be reduced / modified.

[0107] Once one or more CBCT scan files are uploaded and associated with the patient, the physician can select the CBCT scan when filling out the patient's prescription form to perform dental treatment and can submit prescription form 1105. This can be done through a part of the physician system / subsystem (as referenced below). Figure 12 (As described), and may include a physician-oriented user interface that allows physicians to select the use of CBCT scans as part of treatment planning preparation. As part of this step, a user interface, which may be a patient management portal or a part thereof, may provide patient-specific sales order quotes including CBCT-related prescriptions 1106. In some cases, the patient management portal may include or be part of a patient system, as follows: Figure 12As described in more detail below. A patient management portal (e.g., a physician-oriented user interface) can create sales orders with patient-specific (e.g., unique) identifiers associated with a particular user and / or physician. This process can also be integrated into a treatment planning system and / or a device manufacturing system / subsystem (e.g., a manufacturing execution system) 1107. The patient management portal can synchronously access a data store 1108 containing CBCT information and / or any additional data specific to the patient and scans (e.g., CBCT scans, intraoral scans, etc.) and can present (“publish”) a link between a sales order quote and an actual sales order 1109.

[0108] A system that includes a module that can coordinate accessed CBCT information and physician prescriptions can attach (or link) pre-processed (e.g., segmented) CBCT scan data to a sales order and can internally register the CBCT-related portion of a prescription, making it available to the customer for retrieval / modification. This can be part of the same physician-facing subsystem (e.g., a patient management portal) or a separate module.

[0109] Subsequently, the system can perform initial fusion of CBCT and intraoral scans. The CBCT scan fusion engine can be invoked by the treatment planning system and can be accessed or triggered by the treatment planning and / or manufacturing subsystems 1111. This step can be performed after the client (e.g., physician) has completed modifications and / or accepted a sales order (e.g., step 1110). This process can trigger the treatment planning system 1112.

[0110] Subsequently, the CBCT scan fusion engine can fuse tooth roots from CBCT scans with crowns from intraoral scans, and can further process the virtual model of the patient's dentition in other ways. This can include further annotation of the digital model of the patient's dentition (including labeling one or more features, identifying patient data / metadata, etc.).

[0111] Optionally, the process may include an additional detailed description of the digital model. This detailed description may be automated, semi-automated (e.g., technician / physician assisted and / or approved), or manual 1114. The user (e.g., a physician) may approve, reject, and / or suggest additional modifications to the fused digital model as part of the CBCT rejection process 1115, which may be a manual step. Optionally, the method may then utilize the digital model in further processing, including automated, semi-automated, or manual subscriptions (S&S) considering the tooth root 1116. Subsequently, the user (e.g., a physician) may use root visualization to examine (one or more) treatment plans and / or the digital model 1117.

[0112] Figure 12This illustration shows a variant of a computing environment 1200 that can generate one or more orthodontic / dental instruments and / or patient-specific treatment plans, and manufacture dental instruments, under the guidance of dental professionals, that can realize the treatment plans to treat patients. The computing environment may include the CBCT fusion engine 1290 as described above. Figure 12 The example computing environment 1200 shown includes a dental scanning system (e.g., optionally including an intraoral scanning system 1210 and / or a CBCT scanning system 1215), a physician system 1220, a treatment planning system 1230 (e.g., a technician system), a patient system 1240, an instrument manufacturing system 1250, and a computer-readable medium 1260. Each of these systems can be equivalently referred to as a subsystem of the overall system (e.g., the computing environment). Although shown as discrete systems, some or all of these systems can be integrated and / or combined. In some variations, the computing environment (dental computing system) 1200 may include only one or a subset of these systems (which can also be referred to as a subsystem of the overall system 1200). As mentioned above, one or more of these systems can be combined or integrated with one or more other systems (subsystems), for example, the patient system and physician system may be part of a remote server accessible by a physician and / or patient interface. The computer-readable medium 1260 can be divided among all or some of the systems (subsystems); for example, a treatment planning system and an instrument manufacturing system can be part of the same subsystem and can be located on the computer-readable medium 1260. In addition, each of these systems can be further divided into subsystems or components, which can be physically distributed (e.g., between local and remote processors, etc.) or can be integrated.

[0113] The dental scanning system 1209 may include one or more of the following: an intraoral scanning system 1210 and / or a CBCT scanning system 1215. The intraoral scanning system may include an intraoral scanner and one or more processors for processing images. For example, the intraoral scanning system 1210 may include optics 1211 (e.g., one or more lenses, filters, mirrors, etc.), one or more processors 1212, a memory 1213, and a scan capture module 1214. Typically, the intraoral scanning system 1210 can capture one or more images of a patient's dentition. The use of the intraoral scanning system 1210 may be in a clinical setting (such as a doctor's office) or in an environment of the patient's choice (e.g., the patient's home). In some cases, the operation of the intraoral scanning system 1210 may be performed by an intraoral scanner, a dental camera, a mobile phone, or any other feasible device.

[0114] Optical component 1211 may include one or more lenses and optical sensors to capture reflected light, particularly reflected light from the patient's dental arch. Scan capture module 1214 may include instructions (such as non-transitory computer-readable instructions) that can be stored in memory 1213 and executed by processor(s) 1212 to control the capture of any number of images of the patient's dental arch.

[0115] exist Figure 12 In this context, segmentation 1232 and validation 1232 (e.g., classifier engine 1243) are shown as part of treatment planning subsystem 1230; however, in some examples, some or all of these components may be part of (or replicated in) dental scanning system 1209. For example, segmentation module 1232 may be in intraoral scanning subsystem 1210, or another subsystem may be in treatment planning subsystem 1230 or some other subsystem. Any component system or subsystem of dental computing environment 1200 may access or use the segmented data. Similarly, tooth axis setting module 1261 and / or tooth numbering module 1263 may be part of treatment planning subsystem 1230; however, in some examples, some or all of these components may be part of (or replicated in) dental scanning system 1209.

[0116] The physician system 1220 (e.g., a physician subsystem) may include a treatment management module 1221 and an intraoral state capture module 1222, which can access or use 3D models based on segmented data. The physician system 1220 may provide a "physician-oriented" interface to the computing environment 1200. The treatment management module 1221 can perform any operations that enable a physician or other clinician to manage the treatment of any patient. In some examples, the treatment management module 1221 may provide visualization and / or simulation of the patient's dentition relative to a treatment plan. The user interface may also include display segments.

[0117] The intraoral state capture module 1222 can provide clinicians with images of the patient's dentition via the physician system 1220. These images can be captured by the dental scanning system 1209 and may also include simulated images of tooth movement based on treatment planning.

[0118] In some examples, the treatment management module 1221 may enable the physician to modify or revise the treatment plan, particularly when images provided by the intraoral state capture module 1222 indicate that the movement of the patient's teeth may not be in accordance with the treatment plan. The physician system 1220 may include one or more processors configured to execute any feasible non-transitory computer-readable instructions to perform any feasible operations described herein.

[0119] Alternatively or additionally, the treatment planning system 1230 may include any of the methods and devices described herein, including the CBCT fusion engine 1290. Although the CBCT fusion engine 1290 is shown as part of the treatment planning system 1230, the CBCT fusion engine may be separate and may communicate directly or indirectly with the physician system 1220 and / or the treatment planning system 1230, or any other system or subsystem shown.

[0120] Treatment planning system 1230 may include a scan processing / detailed description module 1231, a segmentation module 1232, one or more classifier engines 1243, a phased module 1233, a treatment monitoring module 1234, and one or more treatment planning data storage units 1235. Typically, treatment planning system 1230 can determine a treatment plan for any feasible patient. Scan processing / detailed description module 1231 may receive or acquire dental scans (such as scans from dental scanning system 1209) and may process the scans to "clean" them by removing scan errors and, in some cases, enhancing the detail of the scan images. Treatment planning system 1230 may perform segmentation. For example, treatment planning system may include segmentation module 1232, which may segment a dental model into individual parts including individual teeth, gingiva, jawbone, etc. In some cases, the dental model may be based on scan data from scan processing / detailed description module 1231 (and / or classifier engine 1243).

[0121] The phased module 1233 can define different stages of the treatment plan. Each stage can correspond to a different dental appliance. The phased module 1233 can also determine the final position of the patient's teeth based on the treatment plan. Therefore, the phased module 1233 can determine some or all of the patient's orthodontic treatment plan. In some examples, the phased module 1233 can simulate the movement of the patient's teeth according to the different stages of the patient's treatment plan.

[0122] Optional treatment monitoring module 1234 can monitor the progress of orthodontic treatment planning. In some examples, treatment monitoring module 1234 can provide clinicians with an analysis of the progress of treatment planning. Although not shown here, treatment planning system 1230 may include one or more processors configured to execute any feasible non-transitory computer-readable instructions to perform any feasible operations described herein.

[0123] Tooth axis setting module 1261 and / or tooth numbering module 1263 may be included as part of treatment planning subsystem 1230 as discussed above, and may include features and perform the steps described above for tooth numbering / setting or verification and / or for tooth axis determination, setting and / or verification.

[0124] The patient system 1240 may include a treatment visualization module 1241 and an intraoral state capture module 1242. Typically, the patient system 1240 may provide a "patient-oriented" interface to the computing environment 1200. The treatment visualization module 1241 enables the patient to visualize how the orthodontic treatment plan is progressing and also visualizes the predicted results (e.g., the final position of the teeth).

[0125] In some examples, the patient system 1240 may capture a dental scan of the treatment visualization module 1241 via an intraoral state capture module 1242. The intraoral state capture module enables the patient to capture his or her own dental arch via a dental scanning system 1209. Although not shown here, the patient system 1240 may include one or more processors configured to execute any feasible non-transitory computer-readable instructions to perform any feasible operations described herein.

[0126] The instrument manufacturing system 1250 may include an instrument manufacturing machine 1251, one or more processors 1252, a memory 1253, and an instrument generation module 1254. Typically, the instrument manufacturing system 1250 can directly or indirectly manufacture orthodontic appliances to implement orthodontic treatment planning. In some examples, orthodontic treatment plans may be stored in one or more treatment planning data storage units 1235. Any of these devices and methods may be configured to include steps of manufacturing one or more (e.g., a series) dental instruments using 3D models, including, for example, correction segments as described herein.

[0127] The instrument manufacturing machine 1251 may include any feasible implementation or device capable of manufacturing any suitable dental appliance. The instrument generation module 1254 may include any non-transitory computer-readable instructions that, when executed by one or more processors 1252, can instruct the instrument manufacturing machine 1251 to produce one or more dental appliances. The memory 1253 may store data or instructions for use by one or more processors 1252. In some examples, the memory 1253 may temporarily store treatment plans, dental models, or intraoral scans.

[0128] Computer-readable medium 1260 may include some or all of the elements described herein with respect to computing environment 1200. Computer-readable medium 1260 may include non-transitory computer-readable instructions that, when executed by a processor, can provide the functionality of any apparatus, machine, or module described herein.

[0129] All publications and patent applications mentioned in this specification are incorporated herein by reference in their entirety, to the extent that each individual publication or patent application is specifically and individually indicated to be incorporated herein by reference. Furthermore, it should be understood that all combinations of the foregoing concepts and the additional concepts discussed below in more detail (provided these concepts are not contradictory) are contemplated as part of the inventive subject matter disclosed herein and can be used to achieve the benefits described herein.

[0130] Any of the methods described herein (including user interfaces) can be implemented as software, hardware, or firmware, and can be described as a non-transitory computer-readable storage medium storing a set of instructions executable by a processor (e.g., a computer, tablet, smartphone, etc.), which, when executed by the processor, causes the processor to control any one of the execution steps, including but not limited to: displaying, communicating with the user, analyzing, modifying parameters (including timing, frequency, intensity, etc.), determining, issuing warnings, etc. For example, any of the methods described herein can be executed at least in part by a device comprising one or more processors having a memory storing a non-transitory computer-readable storage medium storing a set of instructions for one or more processes of the method.

[0131] While various embodiments are described and / or illustrated herein in the context of a full-featured computing system, one or more of these example embodiments may be allocated as a program product in various forms, regardless of the specific type of computer-readable medium used to actually perform that allocation. The embodiments disclosed herein may also be implemented using software modules that perform certain tasks. These software modules may include scripts, batch files, or other executable files that may be stored on computer-readable storage media or in a computing system. In some embodiments, these software modules may configure the computing system to perform one or more of the example embodiments disclosed herein.

[0132] As described herein, the computing devices and systems described and / or illustrated herein broadly represent any type or form of computing device or system capable of executing computer-readable instructions, such as those contained within the modules described herein. In their most basic configuration, these computing devices may each include at least one memory device and at least one physical processor.

[0133] As used herein, the term "memory" or "memory device" generally refers to any type or form of volatile or non-volatile storage device or medium capable of storing data and / or computer-readable instructions. In one example, a memory device may store, load, and / or maintain one or more modules described herein. Examples of memory devices include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, hard disk drive (HDD), solid-state drive (SSD), optical disk drive, cache, variations or combinations thereof, or any other suitable storage memory.

[0134] Furthermore, as used herein, the term "processor" or "physical processor" generally refers to a processing unit of any type or form of hardware implementation capable of interpreting and / or executing computer-readable instructions. In one example, a physical processor may access and / or modify one or more modules stored in the aforementioned memory device. Examples of physical processors include, but are not limited to, microprocessors, microcontrollers, central processing units (CPUs), field-programmable gate arrays (FPGAs) implementing soft-core processors, application-specific integrated circuits (ASICs), multiple portions of one or more of these, variations or combinations thereof, or any other suitable physical processor.

[0135] Although shown as separate elements, the method steps described and / or illustrated herein may represent multiple parts of a single application. Furthermore, in some embodiments, one or more of these steps may represent or correspond to one or more software applications or programs that, when executed by a computing device, enable the computing device to perform one or more tasks, such as the method steps.

[0136] Furthermore, one or more devices described herein can transform data, physical devices, and / or representations of physical devices from one form to another. Additionally or alternatively, one or more modules described herein can transform a processor, volatile memory, non-volatile memory, and / or any other part of the physical computing device from one form of computing device to another through data executed on the computing device, stored on the computing device, and / or otherwise interacting with the computing device.

[0137] As used herein, the term "computer-readable medium" generally refers to any form of device, carrier, or medium capable of storing or carrying computer-readable instructions. Examples of computer-readable media include, but are not limited to, transmissive media (such as carrier waves) and non-transient media (such as magnetic storage media (e.g., hard disk drives, magnetic tape drives, and floppy disks), optical storage media (e.g., compact discs (CDs), digital video optical discs (DVDs), and Blu-ray discs), electronic storage media (e.g., solid-state drives and flash memory media), and other distributed systems.

[0138] Those skilled in the art will recognize that any process or method disclosed herein can be modified in various ways. The process parameters and order of steps described and / or illustrated herein are given by way of example only and can be changed as needed. For example, while the steps shown and / or described herein may be shown or discussed in a particular order, these steps do not necessarily have to be performed in the order shown or discussed.

[0139] The various exemplary methods described and / or illustrated herein may omit one or more steps described or illustrated herein, or may include additional steps beyond those disclosed. Furthermore, the steps of any method disclosed herein may be combined with any one or more steps of any other method disclosed herein.

[0140] The processor described herein can be configured to perform one or more steps of any of the methods disclosed herein. Alternatively or in combination, the processor can be configured to combine one or more steps of one or more methods disclosed herein.

[0141] When a feature or element is referred to herein as being “on” another feature or element, it may be directly located on the other feature or element, or there may be intermediary features and / or elements present. Conversely, when a feature or element is referred to as being “directly on” another feature or element, there is no intermediary feature or element. It should also be understood that when a feature or element is referred to as being “connected,” “attached,” or “joined” to another feature or element, it may be directly connected, attached, or joined to the other feature or element, or there may be intermediary features or elements present. Conversely, when a feature or element is referred to as being “directly connected,” “directly attached,” or “directly joined” to another feature or element, there is no intermediary feature or element. Although described or illustrated with reference to one embodiment, the features and elements thus described or illustrated may be applied to other embodiments. Those skilled in the art will also recognize that references to structures or features provided “adjacent” to another feature may have portions overlapping with or beneath the adjacent feature.

[0142] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. For example, unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein are intended to include the plural forms as well. It should also be understood that the terms “comprises” and / or “comprising” as used in this specification designate the presence of stated features, steps, operations, elements, and / or components, but do not exclude 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 associated listed items and may be abbreviated to “ / ”.

[0143] Furthermore, for ease of description, spatially relative terms such as “below,” “under,” “lower,” “above,” and “higher” may be used in the specification to describe the relationship of one component or feature to one or more other components or features, as illustrated in the figures. It should be understood that, in addition to the orientation depicted in the figures, spatially relative terms are intended to cover different orientations of the device in use or operation. For example, if the device in the inverted figure is described as being “below” or “under” other elements or features, it will be oriented “above” other elements or features. Thus, the exemplary term “below” can encompass both “above” and “below” orientations. The device may be oriented in other ways (rotated 90 degrees or otherwise), and the spatially relative descriptive language used herein should be interpreted accordingly. Similarly, unless otherwise specified, the terms “upward,” “downward,” “vertically,” “horizontally,” and similar terms used herein are for illustrative purposes only.

[0144] 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 otherwise requires. These terms may be used to distinguish one feature / element from another. Therefore, without departing from the teachings of the invention, the first feature / element discussed below may be referred to as the second feature / element, and similarly, the second feature / element discussed below may be referred to as the first feature / element.

[0145] Generally, the devices and methods described herein should be understood as inclusive, but all or a subset of the components and / or steps may instead be exclusive and may be expressed as “consisting of various components, steps, sub-components or sub-steps” or alternatively “consisting substantially of various components, steps, sub-components or sub-steps”.

[0146] As used herein in the specification and claims, including in the examples, all figures may be read as if they begin with the words “about” or “approximately”, even if the term is not explicitly stated. The phrase “about” or “approximately” may be used when describing magnitude and / or location to indicate that the described value and / or location is within a reasonably expected range of value and / or location. For example, a numerical value may have values ​​such as + / -0.1% of a set value (or range of values), + / -1% of a set value (or range of values), + / -2% of a set value (or range of values), + / -5% of a set value (or range of values), + / -10% of a set value (or range of values), etc. Unless the context otherwise requires, any numerical value given herein should also be understood to include approximately or about that value. For example, if the value “10” is disclosed, “about 10” is also disclosed. Any numerical range described herein is intended to include all subranges contained therein. It should also be understood that, as those skilled in the art would appropriately understand, when a value is disclosed as "less than or equal to" that value, "greater than or equal to" that value and the possible range between the value are also disclosed. For example, if the value "X" is disclosed, then "less than or equal to X" and "greater than or equal to X" (e.g., where X is a numerical value) are also disclosed. It should also be understood that throughout the application, data is provided in a variety of different formats, and this data represents the endpoints and start points, as well as the ranges, for any combination of data points. For example, if a specific data point "10" and a specific data point "15" are disclosed, it should be understood that greater than, greater than or equal to, less than, less than or equal to, and equal to 10 and 15 are considered to be disclosed in the same way as between 10 and 15. It should also be understood that every unit between two specific units is also disclosed. For example, if 10 and 15 are disclosed, then 11, 12, 13, and 14 are also disclosed.

[0147] Although various illustrative embodiments have been described above, any of a number of changes may be made to the various embodiments without departing from the scope of the invention as described in the claims. Optional features of the various apparatus and system embodiments may be included in some embodiments but not in others. Therefore, the foregoing description is provided primarily for illustrative purposes and should not be construed as limiting the scope of the invention as set forth in the claims.

[0148] The examples and illustrations included herein show specific embodiments in which the subject matter can be practiced by way of illustration and not limitation. As stated above, other embodiments can be utilized and derived therefrom, allowing for structural and logical substitutions and changes without departing from the scope of this disclosure. For convenience only, such embodiments of the inventive subject matter may be referred to herein individually or collectively by the term "invention" and are not intended to actively limit the scope of this application to any single invention or inventive concept, if in fact more than one is disclosed. Therefore, although specific embodiments have been illustrated and described herein, any arrangement contemplated to achieve the same purpose may replace the specific embodiments shown. This disclosure is intended to cover any and all modifications or variations of the various embodiments. Upon review of the above description, those skilled in the art will understand combinations of the above embodiments and other embodiments not specifically described herein.

Claims

1. A method for fusing cone-beam computed tomography (CBCT) scans with intraoral scans, the method comprising: The remote processing agent receives the processed CBCT scan file from the patient, which has already been processed by the local processing agent through the following steps: Remove one or more regions in the processed CBCT scan file that correspond to one or more regions in the patient's CBCT scan file that correspond to the region outside any tooth root, and / or pre-segment the CBCT scan in the processed CBCT scan file by the remote processing agent to ensure that the processed CBCT scan file can be segmented into individual tooth roots in volume based on the scan quality of the CBCT scan, and reject patient CBCT scan files that cannot be segmented. as well as The CBCT scans from the processed CBCT scan files are fused with intraoral scans of the crowns of the patient's teeth to form a final model of the patient's teeth including the roots, wherein the processed CBCT scans have been segmented in volume and the intraoral scans have been segmented in surface.

2. The method according to claim 1, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been processed to limit the file size to less than the maximum file size, wherein the file size is limited to less than the maximum file size by truncating the patient's CBCT scan file to remove one or more regions outside the region containing the tooth root.

3. The method according to claim 1, wherein, Receiving a processed CBCT scan file includes receiving a processed CBCT scan file that has been processed to limit its file size to less than a maximum file size, wherein the file size is limited to less than the maximum file size by truncating the patient's CBCT scan file to remove one or more layers of the patient's CBCT scan file.

4. The method according to claim 1, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been pre-segmented, wherein the CBCT scan files are pre-segmented based on scan quality to reject blurry and / or CBCT scan files that cannot be segmented based on scan quality.

5. The method according to claim 1, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been pre-segmented, wherein the CBCT scan files are pre-segmented by applying a trained neural network to determine whether the CBCT scan files can be segmented, wherein the trained neural network is trained on a database of CBCT scans with different scan qualities.

6. The method according to claim 1, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been segmented in volume by a local processing agent.

7. The method according to claim 1 further includes segmenting the received processed CBCT scan file by volume.

8. The method according to claim 1 further includes segmenting the intraoral scan.

9. The method according to claim 1, wherein, The fusion involves matching segmented intraoral scan crown regions with segmented CBCT scan crown regions and replacing segmented CBCT scan crown regions with segmented intraoral scan crown regions.

10. The method according to claim 1, wherein, The fusion was validated by assessing the degree of matching between the crown regions of segmented intraoral scans and segmented CBCT scans.

11. The method of claim 1, further comprising using the root axis of each tooth to determine the long axis of each tooth in the final model.

12. The method of claim 1, further comprising displaying a final model of the patient's teeth in a user interface configured to allow the user to interactively display a subset of segmented regions of the final model.

13. The method according to claim 12, wherein, Allowing users to interactively display subsets of segmented regions includes receiving user commands to show one or more of the following: unerupted teeth, roots only, surrounding translucent bone, and crowns only.

14. The method according to claim 1, wherein, CBCT scan files include Medical Digital Imaging and Communications (DICOM) files.

15. A method for fusing cone-beam computed tomography (CBCT) scans with intraoral scans, the method comprising: In the remote processing agent, a processed CBCT scan file that has been processed by the local processing agent through the following steps is received: preparing the processed CBCT scan file from the CBCT scan file of the patient, including adjusting the processed CBCT scan file to remove one or more areas outside any tooth root, and performing pre-segmentation to ensure that the processed CBCT scan file can be segmented into individual tooth roots in volume based on the scan quality of the CBCT scan, and rejecting CBCT scan files that cannot be segmented; In the remote processing agent, the processed CBCT scan file is segmented; Segmented CBCT scans are fused with segmented intraoral scans of the patient's tooth crowns to create a final model of the patient's tooth, including the roots.

16. A non-transitory computing device readable medium having instructions stored thereon, the instructions being executable by a processor of a remote processing agent to cause the remote processing agent to perform a method comprising the steps of: Receive the processed CBCT scan file that has been processed by the local processing agent through the following steps: Remove one or more regions in the processed CBCT scan file that correspond to one or more regions in the patient's CBCT scan file that correspond to the region outside any tooth root, and / or have the CBCT scan in the processed CBCT scan file pre-segmented by a remote processing agent to ensure that the processed CBCT scan file can be volumetrically segmented into individual tooth roots based on the scan quality of the CBCT scan, and reject patient CBCT scan files that cannot be segmented; and The CBCT scans from the processed CBCT scan files were fused with intraoral scans of the patient's tooth crowns to create a final model of the patient's tooth, including the roots. The processed CBCT scans have been segmented in volume and the intraoral scans have been segmented on the surface.

17. The non-transitory computing device readable medium according to claim 16, wherein, Preparing patient CBCT scan files includes limiting the file size of the patient CBCT scan files to less than the maximum file size.

18. The non-transitory computing device readable medium according to claim 16, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been processed to limit the file size to less than the maximum file size, wherein the file size is limited to less than the maximum file size by truncating the patient's CBCT scan file to remove one or more regions outside the region containing the tooth root.

19. The non-transitory computing device readable medium according to claim 16, wherein, Receiving a processed CBCT scan file includes receiving a processed CBCT scan file that has been processed to limit its file size to less than a maximum file size, wherein the file size is limited to less than the maximum file size by truncating the patient's CBCT scan file to remove one or more layers of the patient's CBCT scan file.

20. The non-transitory computing device readable medium according to claim 16, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been pre-segmented, wherein the CBCT scan files are pre-segmented based on scan quality to reject blurry and / or CBCT scan files that cannot be segmented based on scan quality.

21. The non-transitory computing device readable medium according to claim 16, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been pre-segmented, wherein the CBCT scan files are pre-segmented by applying a trained neural network to determine whether the CBCT scan files can be segmented, wherein the trained neural network is trained on a database of CBCT scans with different scan qualities.

22. The non-transitory computing device readable medium according to claim 16, wherein, Receiving processed CBCT scan files includes receiving processed CBCT scan files that have been segmented in volume by a local processing agent.

23. The non-transitory computing device readable medium according to claim 16, wherein, The instructions are also configured to cause the remote processor to segment the received, processed CBCT scan file by volume.

24. The non-transitory computing device readable medium according to claim 16, wherein, The instruction is also configured to cause the remote processor to segment the in-port scan.

25. The non-transitory computing device readable medium according to claim 16, wherein, The fusion involves matching segmented intraoral scan crown regions with segmented CBCT scan crown regions and replacing segmented CBCT scan crown regions with segmented intraoral scan crown regions.

26. The non-transitory computing device readable medium according to claim 16, wherein, The fusion was validated by assessing the degree of matching between the crown regions of segmented intraoral scans and segmented CBCT scans.

27. The non-transitory computing device readable medium according to claim 16, wherein, The instructions are also configured to enable the remote processor to use the root axis of each tooth to determine the long axis of each tooth in the final model.

28. The non-transitory computing device readable medium according to claim 16, wherein, The instructions are also configured to cause the remote processor to display a final model of the patient's teeth in a user interface configured to allow the user to interactively display a subset of segmented regions of the final model.

29. The non-transitory computing device readable medium according to claim 28, wherein, Allowing users to interactively display subsets of segmented regions includes receiving user commands to show one or more of the following: unerupted teeth, roots only, surrounding translucent bone, and crowns only.

30. A non-transitory computing device readable medium having instructions stored thereon, the instructions being executable by a processor of a remote processing agent to cause the remote processing agent to perform a method comprising the steps of: In the remote processing agent, the processed CBCT scan file that has been processed by the local processing agent through the following steps is received: the file size of the patient's CBCT scan file is limited to less than the maximum file size by removing one or more areas outside any tooth root through file truncation, and pre-segmentation is performed to ensure that the processed CBCT scan file can be segmented into individual tooth roots in volume based on the scan quality of the CBCT scan, and CBCT scan files that cannot be segmented are rejected. In the remote processing agent, the processed CBCT scan file is segmented; Segmented CBCT scans are fused with segmented intraoral scans of the patient's tooth crowns to create a final model of the patient's tooth, including the roots.

31. A method for processing cone-beam computed tomography (CBCT) scans, the method comprising: Use local software to process proxy access to patient CBCT scan files; Processed CBCT scans are generated from patient CBCT scans; The file size of the processed CBCT scan files is limited to be smaller than the maximum file size; The remote processing agent pre-segments the CBT scans in the processed CBCT scan files to ensure that the processed CBCT scan files can be segmented into individual tooth roots in volume based on the scan quality of the CBCT scans, and rejects CBCT scan files that cannot be segmented. as well as The processed CBCT scan files are uploaded to a remote site for fusion with intraoral scans from the patient.

32. The method according to claim 31, wherein, Limiting file size includes truncating CBCT scan files to remove one or more areas outside the region containing the tooth root.

33. The method according to claim 31, wherein, Limiting file size includes truncating patient CBCT scan files to remove one or more layers from the patient CBCT scan file.

34. The method according to claim 31, wherein, Pre-segmentation of CBCT scan files based on scan quality includes rejecting blurry and / or below-minimum resolution CBCT scan files that cannot be segmented based on scan quality.

35. The method according to claim 31, wherein, Pre-segmentation of CBCT scan files based on scan quality involves applying a trained neural network to determine whether a CBCT scan file can be segmented. The trained neural network is trained on a database of CBCT scans with different scan qualities.

36. The method of claim 31 further includes segmenting the processed CBCT scan file by volume using a local processing agent.

37. The method according to claim 31, wherein, Uploading processed CBCT scan files involves segmenting the processed CBCT scan files by a remote processing agent.

38. The method according to claim 31, wherein, CBCT scan files include Medical Digital Imaging and Communications (DICOM) files.

39. The method of claim 31, further comprising displaying one or more messages to the user regarding the scan quality of the CBCT scan file before uploading the processed CBCT scan file.

40. A method for processing cone-beam computed tomography (CBCT) scans, the method comprising: The local software processing agent is used to generate processed CBCT scans from patient CBCT scans; By truncating CBCT scan files to remove one or more regions of the CBCT scan file containing the tooth root, the file size of the processed CBCT scan file is limited to less than the maximum file size. The CBT scan of the processed CBCT scan file is pre-segmented by a remote processing agent to ensure that the processed CBCT scan file can be segmented into individual tooth roots in volume based on the scan quality of the CBCT scan, and CBCT scan files that cannot be segmented are rejected. The scan quality includes one or more of the following: blur and resolution. as well as The processed CBCT scan files are uploaded to a remote site for fusion with intraoral scans from the patient.

41. A local processing agent for processing cone-beam computed tomography (CBCT) scans, comprising a non-transitory computing device-readable medium thereon storing instructions executable by a processor of a remote processing agent to cause the remote processing agent to perform a method comprising the following steps: Use local software to process proxy access to patient CBCT scan files; Processed CBCT scans are generated from patient CBCT scans; The file size of the processed CBCT scan files is limited to be smaller than the maximum file size; The CBT scan of the processed CBCT scan file is pre-segmented by a remote processing agent to ensure that the processed CBCT scan file can be segmented into individual tooth roots in volume based on the scan quality, and CBCT scan files that cannot be segmented are rejected; and The processed CBCT scan files are uploaded to a remote site for fusion with intraoral scans from the patient.

42. The non-transitory computing device readable medium according to claim 41, wherein, Limiting file size includes truncating CBCT scan files to remove one or more areas outside the region containing the tooth root.

43. The non-transitory computing device readable medium according to claim 41, wherein, Limiting file size includes truncating patient CBCT scan files to remove one or more layers from the patient CBCT scan file.

44. The non-transitory computing device readable medium according to claim 41, wherein, Pre-segmentation of CBCT scan files based on scan quality includes rejecting blurry and / or below-minimum resolution CBCT scan files that cannot be segmented based on scan quality.

45. The non-transitory computing device readable medium according to claim 41, wherein, Pre-segmentation of CBCT scan files based on scan quality involves applying a trained neural network to determine whether a CBCT scan file can be segmented. The trained neural network is trained on a database of CBCT scans with different scan qualities.

46. ​​The non-transitory computing device readable medium according to claim 41, wherein, The instructions are also configured to have the processed CBCT scan files segmented by volume by a local processing agent.

47. The non-transitory computing device readable medium according to claim 41, wherein, CBCT scan files include Medical Digital Imaging and Communications (DICOM) files.

48. A local processing agent for processing cone-beam computed tomography (CBCT) scans, comprising a non-transitory computing device-readable medium thereon storing instructions executable by a processor of a remote processing agent to cause the remote processing agent to perform a method comprising the following steps: Use local software to process proxy access to patient CBCT scan files; By truncating CBCT scan files to remove one or more regions outside the area containing the tooth root, the file size of the CBCT scan file is limited to less than the maximum file size; The CBT scan is pre-segmented by a remote processing agent to ensure that the processed CBCT scan file can be segmented into individual tooth roots based on the scan quality, and CBCT scan files that cannot be segmented are rejected. Scan quality includes one or more of the following: blurriness and resolution; as well as The processed CBCT scan files are uploaded to a remote site for fusion with intraoral scans from the patient.

49. A method comprising: Receive a digital three-dimensional (3D) model of the patient's teeth, wherein the 3D model of the patient's teeth includes a fusion of a CBCT scan of the patient's jaw and an intraoral scan of the patient's crown region of the teeth; For one or more steps in the treatment plan used for orthodontic movement of a patient's teeth, a 3D model of the patient's teeth is used to simulate the movement of the tooth roots relative to the patient's alveolar bone. Identify the formation of one or more windows in the tooth root from simulations of one or more steps in the treatment plan; and The display shows a 3D model of a patient's teeth with one or more windows showing one or more steps in the treatment plan.

50. The method of claim 49, further comprising receiving one or more modifications to the treatment plan from a user; and simulating the movement of the tooth root relative to the patient's alveolar bone, and displaying a 3D model of the patient's tooth showing the identified one or more windowed modifications.

51. The method of claim 49, further comprising receiving a command from a user to open a display window.

52. The method according to claim 51, wherein, The received commands include interactively switching between stages of treatment planning based on user input and displaying a 3D model of one or more identified fenestrated patient teeth.

53. The method of claim 49, further comprising identifying the formation of one or more cracks in the tooth root from a simulation of one or more steps of the treatment plan, and displaying a 3D model of the patient tooth showing the identified one or more cracks in one or more steps of the treatment plan.

54. The method of claim 49, further comprising identifying the formation of one or more protrusions of the tooth root relative to the alveolar bone in a simulation of one or more steps of the treatment plan, and displaying a 3D model of the patient's tooth illustrating the identified one or more protrusions for one or more steps of the treatment plan.

55. The method according to claim 49, wherein, The simulation involves determining the long axis of each tooth using the long axis of the root portion of each tooth from the 3D model, and modeling the motion of the tooth root based on the force applied to the crown of the tooth and the relative position of adjacent teeth including the root portions of adjacent teeth.

56. A method comprising: Receive a digital three-dimensional (3D) model of the patient's teeth, wherein the 3D model of the patient's teeth includes a fusion of a CBCT scan of the patient's jaw and an intraoral scan of the patient's crown region of the teeth; For one or more steps in the treatment plan used for orthodontic movement of a patient's teeth, a 3D model of the patient's teeth is used to simulate the movement of the tooth roots relative to the patient's alveolar bone. Identify the formation of one or more windows in the tooth root from simulations of one or more steps in the treatment plan; Receive a command from the user to open a window; The display shows a 3D model of a patient's teeth with one or more windows identified, representing one or more steps in the treatment plan; Receive one or more modifications to the treatment plan from the user; and The simulation of the movement of the modified tooth root relative to the patient's alveolar bone is shown, and a 3D model of one or more identified modified patient teeth with windows is displayed.

57. A method comprising: Receive a digital three-dimensional (3D) model of the patient's teeth, wherein the 3D model of the patient's teeth includes a fusion of a CBCT scan of the patient's jaw and an intraoral scan of the patient's crown region of the teeth; For one or more steps in the treatment plan used for orthodontic movement of a patient's teeth, a 3D model of the patient's teeth is used to simulate the movement of the tooth roots relative to the patient's alveolar bone. Identify the formation of one or more alveolar bone defects, said one or more alveolar bone defects including one or more of the following: fenestration of a simulated root from one or more steps of the treatment plan, cracking of a simulated root from one or more steps of the treatment plan, and one or more protrusions of a simulated root relative to the alveolar bone from one or more steps of the treatment plan, and display a 3D model of the patient's tooth showing the identified one or more protrusions from one or more steps of the treatment plan; and The display shows a 3D model of a patient's teeth illustrating one or more steps in the treatment plan for one or more identified alveolar bone defects.

58. A non-transitory computing device readable medium having instructions stored thereon, the instructions being executable by a processor of a remote processing agent to cause the remote processing agent to perform a method comprising the steps of: Receive the processed CBCT scan file that has been processed by the local processing agent through the following steps: Receive a digital three-dimensional (3D) model of the patient's teeth, where, The 3D model of the patient's teeth is a fusion of CBCT scans of the patient's jaw and intraoral scans of the patient's crown region of the teeth; For one or more steps in the treatment plan used for orthodontic movement of a patient's teeth, a 3D model of the patient's teeth is used to simulate the movement of the tooth roots relative to the patient's alveolar bone. Identify the formation of one or more windows in the tooth root from simulations of one or more steps in the treatment plan; as well as The display shows a 3D model of a patient's teeth with one or more windows showing one or more steps in the treatment plan.

59. The non-transitory computing device readable medium according to claim 58, wherein, The method also includes receiving one or more modifications to the treatment plan from the user; and simulating the movement of the modified tooth root relative to the patient's alveolar bone, and displaying a 3D model of the patient's tooth with one or more windows identified as modifications.

60. The non-transitory computing device readable medium according to claim 58, wherein, The method also includes receiving a command from the user to open a window.

61. The non-transitory computing device readable medium according to claim 60, wherein, The received commands include interactively switching between stages of treatment planning based on user input and displaying a 3D model of one or more identified fenestrated patient teeth.

62. The non-transitory computing device readable medium according to claim 58, wherein, The method also includes identifying the formation of one or more cracks in the tooth root from simulations of one or more steps of the treatment plan, and displaying a 3D model of the patient tooth showing one or more of the identified cracks in the treatment plan.

63. The non-transitory computing device readable medium according to claim 58, wherein, The method also includes identifying the formation of one or more protrusions of the tooth root relative to the alveolar bone in a simulation of one or more steps of the treatment plan, and displaying a 3D model of the patient's tooth showing the identified one or more protrusions at one or more steps of the treatment plan.

64. The non-transitory computing device readable medium according to claim 58, wherein, The simulation involves determining the long axis of each tooth using the long axis of the root portion of each tooth from the 3D model, and modeling the motion of the tooth root based on the force applied to the crown of the tooth and the relative position of adjacent teeth including the root portions of adjacent teeth.

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