Method for orthodontic treatment planning and manufacturing position correction device and associated apparatus

Abstract

Methods and related apparatus for orthodontic treatment planning and manufacturing position correction devices. The method for orthodontic treatment planning includes acquiring three-dimensional data from a scan of a patient's maxillary surface and dental anatomy and calculating a head shadow measurement from the acquired three-dimensional data. The method processes the calculated head shadow measurements and generates an indicator indicative of tooth positioning along a dental arch of the patient. The generated indicators are analyzed to calculate a desired movement vector for each tooth within the dental arch. The calculated desired motion vector is displayed, stored, or transmitted.

Description

[0001] This application is a divisional application of a Chinese national phase patent application with application number 201880069998.7, which entered the Chinese national phase on April 27, 2020, from a PCT application with international application number PCT / US2018 / 048070, international filing date of August 27, 2018, and invention title "Optimization Methods in Orthodontic Applications".

[0002] Cross - reference to related applications

[0003] This application claims the benefit of U.S. Provisional Application No. 62 / 550,013, filed on August 25, 2017, in the name of Shoupu Chen et al. and titled "METHOD OF OPTIMIZATION IN ORTHODONTIC APPLICATIONS", which is incorporated herein by reference in its entirety. Technical field

[0004] The present invention generally relates to image processing in x - ray computed tomography and, more particularly, to biometric analysis based on 3D images for guidance in orthodontic treatment. Background art

[0005] Cephalometric analysis is the study of dental and skeletal relationships of the head and is used by dentists and orthodontists as a means of evaluating and planning treatment for patients. Conventional cephalometric analysis identifies bone and soft - tissue landmarks in 2D cephalometric radiographs in order to diagnose facial features and deformities before treatment or to gauge treatment progress.

[0006] For example, the main deformities that can be identified in cephalometric analysis are anteroposterior malocclusion problems, which are related to the skeletal relationship between the maxilla and the mandible. Malocclusions are classified based on the relative position of the maxillary first molar. For Class I, neutral occlusion, the molar relationship is normal, but other teeth may have problems such as gaps, crowding, or over - eruption or under - eruption. For Class II, distoclusion, the mesiobuccal cusp of the maxillary first molar rests between the first mandibular molar and the second premolar. For Class III, mesioclusion, the mesiobuccal cusp of the maxillary first molar is posterior to the mesiobuccal groove of the mandibular first molar.

[0007] The exemplary conventional 2D cephalometric analysis method described by Steiner in the article titled "Cephalometries in Clinical Practice" (a paper read at the Charles H. Tweed Foundation for Orthodontic Research, October 1956, pages 8-29) uses angular measurements to evaluate the maxilla and mandible with respect to the cranial base. In the described protocol, Steiner selected four landmarks: nasion, point A, point B, and sella turcica. Nasion is the intersection between the frontal bone of the skull and the two nasal bones. Point A is considered the anterior boundary of the alveolar seat of the maxilla. Point B is considered the anterior boundary of the alveolar seat of the mandible. Sella turcica is at the midpoint of the Turkish saddle. The angle SNA (from sella to nasion and then to point A) is used to determine whether the maxilla is positioned anterior or posterior to the cranial base; a reading of approximately 82 degrees is considered normal. The angle SNB (from sella to nasion and then to point B) is used to determine whether the mandible is positioned anterior or posterior to the cranial base; a reading of approximately 80 degrees is considered normal.

[0008] Recent orthodontic research indicates that the results provided by conventional 2D cephalometric analysis have recurring inaccuracies and inconsistencies. A notable study was titled "In vivo comparison of conventional and cone beam CT synthesized cephalograms" by Vandana Kumar et al. in Angle Orthodontics, September 2008, pages 873-879.

[0009] Due to fundamental limitations in data acquisition, conventional 2D cephalometric analysis mainly focuses on aesthetics and does not focus on the balance and symmetry of the human face. As stated in the article titled "The human face as a 3D model for cephalometric analysis" by Treil et al. in the World Journal of Orthodontics, pages 1-6, planar geometry is not suitable for analyzing anatomical volumes and their growth; only 3D diagnosis can appropriately analyze the anatomical maxillofacial complex. Normal relationships have two more important aspects: balance and symmetry, and when the balance and symmetry of the model are stable, these characteristics define the normal relationship for each individual.

[0010] U.S. Patent No. 6,879,712, titled "System and method of digitally modeling craniofacial features for the purposes of diagnosis and treatment predictions" by Tuncay et al., discloses a method for generating a computer model of craniofacial features. Three-dimensional facial feature data is obtained using laser scanning and digital photographs; dental features are obtained by physically modeling the teeth. The model is laser scanned. Then, skeletal features are obtained from radiographs. The data is combined into a single computer model that can be manipulated and viewed in three dimensions. The model is also capable of forming an animation between the currently modeled craniofacial features and theoretical craniofacial features.

[0011] U.S. Patent No. 6,250,918, titled "Method and apparatus for simulating tooth movement for an orthodontic patient" by Sachdeva et al., discloses a method for determining a 3D direct movement path based on a 3D digital model of an actual orthodontic structure and a 3D model of a desired orthodontic structure. This method uses markers on the laser-scanned crowns and tooth surfaces to scale and simulate tooth movement based on the corresponding three-dimensional direct paths for each tooth. There is no true full-tooth 3D data using the described method.

[0012] Although significant progress has been made towards developing technologies that automate the entry of measurements and the calculation of biometric data for craniofacial features based on such measurements, there is still considerable room for improvement. Even when benefiting from existing means, practitioners require sufficient training to effectively use biometric data. The large amount of measurement and computational data complicates the task of developing and maintaining treatment plans and may increase the risk of human error and oversight.

[0013] Therefore, it can be seen that developing an analytical utility that generates and reports cephalometric results that can assist in guiding orthodontic treatment plans and tracking a patient's progress at different stages of ongoing treatment would be particularly valuable. SUMMARY OF THE INVENTION

[0014] The object of the present disclosure is to address the need for an improved way to analyze 3D anatomical data and apply it to ongoing orthodontic treatment. In view of this object, the present disclosure provides a method for generating an arch form based on a patient's dentition as a guiding means for correcting an orthodontic condition.

[0015] According to one aspect of the present disclosure, there is provided a method at least partially executed by a computer, comprising:

[0016] (a) Obtain three-dimensional data from a scan of the maxillary surface and dental anatomy of a patient;

[0017] (b) Calculate a plurality of cephalometric values based on the obtained three-dimensional data;

[0018] (c) Process the calculated cephalometric values and generate an indicator indicating the tooth positioning along the dental arch of the patient;

[0019] (d) Analyze the generated indicator to calculate the desired movement vectors of the respective teeth within the dental arch;

[0020] And

[0021] (e) Display, store or transmit the calculated desired movement vectors.

[0022] The present disclosure features automatically generating and reporting patient-specific native and optimized geometric primitive parameters and initial quantified tooth movement values for orthodontic treatment.

[0023] Embodiments of the present disclosure combine the skills of a human operator of the system with the computer capabilities for feature identification in a synergistic manner. This utilizes human creativity, heuristic use, flexibility and judgment, and combines these skills with computer advantages such as computational speed, ability for exhaustive and accurate processing, and reporting and data access capabilities.

[0024] These and other aspects, objects, features and advantages of the present disclosure will be more clearly understood and appreciated by reviewing the following detailed description of the preferred embodiments and the appended claims and referring to the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of the embodiments of the disclosure as illustrated in the accompanying drawings. The elements of the drawings are not necessarily drawn to scale relative to each other.

[0026] Figure 1 is a schematic diagram showing an imaging system for providing cephalometric analysis.

[0027] Figure 2 is a logical flow chart showing a process for 3D cephalometric analysis according to an embodiment of the present disclosure.

[0028] Figure 3 is a view of a 3D rendered CBCT head volume image.

[0029] Figure 4 is a view of a 3D rendered tooth volume image after tooth segmentation.

[0030] Figure 5is a view of a user interface displaying three orthogonal views of a CBCT head volume image and operator-entered reference markers.

[0031] Figure 6 is a view of a 3D rendered CBCT head volume image showing a set of 3D reference markers.

[0032] Figure 7A 、 Figure 7B and Figure 7C is a perspective view showing identified anatomical features that provide a framework for cephalometric analysis.

[0033] Figure 8 is a logic flow diagram illustrating the steps for accepting operator instructions for generating a framework for cephalometric analysis.

[0034] Figure 9A 、 Figure 9B and Figure 9C An operator interface is shown for specifying the location of anatomical features using operator-entered reference markers.

[0035] Figure 10A 、 Figure 10B 、 Figure 10C 、 Figure 10D and Figure 10E is a chart showing how various derived parameters are calculated using volumetric image data and corresponding operator-entered reference markers.

[0036] Figure 11 is a 3D graph showing a plurality of derived cephalometric parameters based on the segmented tooth data.

[0037] Figure 12 is a 2D graph showing derived cephalometric parameters from the segmented tooth data.

[0038] Figure 13 is another 3D graph showing derived cephalometric parameters from the segmented tooth data.

[0039] Figure 14 Graphs showing derived cephalometric parameters based on segmented tooth data and treatment parameters.

[0040] Figure 15 is a 3D diagram showing how the system learns tooth picking.

[0041] Figure 16A is a perspective view showing teeth of a digital phantom.

[0042] Figure 16B It is a 3D graph showing the calculation axes of the inertial system of the upper jaw and the lower jaw.

[0043] Figure 17AIt is a chart showing the parallelism of a specific tooth structure.

[0044] Figure 17B It is a chart showing the parallelism of a specific tooth structure.

[0045] Figure 18A It is a perspective view of the teeth of a digital dental model with missing teeth.

[0046] Figure 18B It shows Figure 18A a chart of the calculation axes of the inertial systems of the upper and lower jaws showing an example of

[0047] Figure 19A It is a chart showing the lack of parallelism of a specific tooth structure.

[0048] Figure 19B It is a chart showing the lack of parallelism of a specific tooth structure.

[0049] Figure 20A It is a perspective view of the teeth of a digital dental model with teeth extracted.

[0050] Figure 20B It shows Figure 20A a chart of the calculation axes of the inertial systems of the upper and lower jaws showing an example of

[0051] Figure 21A It is an example showing tooth extraction for missing teeth.

[0052] Figure 21B It shows Figure 21A a chart of the calculation axes of the inertial systems of the upper and lower jaws showing an example of

[0053] Figure 22A It is an example showing tooth extraction for missing teeth.

[0054] Figure 22B It shows Figure 22A a chart of the calculation axes of the inertial systems of the upper and lower jaws showing an example of

[0055] Figure 23A It is an image showing the result of extracting a specific tooth.

[0056] Figure 23B It shows Figure 23A a chart of the calculation axes of the inertial systems of the upper and lower jaws showing an example of

[0057] Figure 24 It shows multiple markers and coordinate axes or vectors of the DOL reference system.

[0058] Figure 25 It shows markers remapped to an alternative space of the DOL reference system.

[0059] Figure 26 A side view shows an example of a tooth inertial system using such a remapping transformation.

[0060] Figure 27 It is a schematic diagram of an independent network for an analysis engine according to an embodiment of the present disclosure.

[0061] Figure 28 It is a schematic diagram of a dependency or coupling network for an analysis engine according to an embodiment of the present disclosure.

[0062] Figure 29 Shows the use of Figure 27 Pseudocode of an algorithm using an independent network arrangement.

[0063] Figure 30 Shows the use of Figure 28 Pseudocode of an algorithm using a dependency network arrangement.

[0064] Figure 31A Lists exemplary parameters as numerical values and their explanations.

[0065] Figure 31B , Figure 31C and Figure 31D Lists exemplary parameters of a specific patient with respect to maxillary facial asymmetry as numerical values and their explanations, where the exemplary parameters are based on exemplary total maxillary facial asymmetry parameters according to an exemplary embodiment of the present application.

[0066] Figure 32A Shows exemplary tabulation results of a specific instance with occlusal analysis and arch angle characteristics.

[0067] Figure 32B Shows exemplary tabulation results of a specific instance of the torque of the upper and lower incisors.

[0068] Figure 32C Shows exemplary tabulation results of another instance with an evaluation of double retraction or double protrusion.

[0069] Figure 32D Shows an exemplary summary list of the results of a cephalometric analysis of a specific patient.

[0070] Figure 32E Shows Figure 35 A detailed list of one of the conditions listed in

[0071] Figure 33 Shows a system display with a recommended message based on the analysis results.

[0072] Figure 34 Shows a system display with a graphical depiction to assist the analysis results.

[0073] Figure 35 An exemplary report showing the asymmetry according to an embodiment of the present disclosure.

[0074] Figure 36 A graph showing the relative left - right asymmetry of a patient in a front view.

[0075] Figure 37 A graph showing the relative overlap of the left and right sides of a patient's face.

[0076] Figure 38 A graph showing facial divergence.

[0077] Figure 39 A logic flow chart showing the logic processing mechanism and data that can be used to provide evaluation and guidance to support orthodontic applications.

[0078] Figure 40 An image showing a typical patient condition (i.e., left rotation of the dental arch).

[0079] Figure 41 A 3D mapping showing the centers of inertia of teeth along the dental arch.

[0080] Figure 42 A plot showing the centers of inertia of teeth arranged along a piece - wise linear curve that connects the centers of inertia in their original positions projected onto a 2D x - y plane.

[0081] Figure 43 Shows for Figure 42 The relative position of an optimized smooth polyline curve for the center of inertia in

[0082] Figure 44 The required movement of teeth from their original positions to desired positions optimized based on the calculations shown and reported.

[0083] Figure 45 A graph showing where the tooth displacement vectors based on the above calculations are indicated.

[0084] Figure 46 A graph showing where the vector displacement is decomposed into tangential and normal directions.

[0085] Figure 47 And Figure 48 Shows the adjustment of a multi - stage tooth arch morphology optimization strategy taken according to the present disclosure.

[0086] Figure 49 A computer - generated list of the movement vectors V of each of the 14 teeth of the dental arch of an orthodontic patient.

[0087] Figure 50AShows the tooth distribution in the initial uncorrected dental arch of an exemplary orthodontic patient.

[0088] Figure 50B Shows the digitally corrected dental arch following the treatment recommendations provided by the system of the present disclosure Figure 50A of the dental arch.

[0089] Figure 50C Shows the overlaid initial dental arch and optimized dental arch in a 3D view, where the initial dental arch is shown as a contour line.

[0090] Figure 50D Shows another example of the initial dental arch in contour line overlaid on the optimized dental arch in a 2D axial view.

[0091] Figure 51 Shows an operator interface display for controlling the process to provide orthodontic data and for displaying the results of the process.

[0092] Figure 52 Is a schematic diagram showing an exemplary manufacturing system for forming an orthodontic appliance using the optimization method of the present disclosure.

[0093] Figure 53 Is a logical flow chart showing a sequence of tasks for applying the results of orthodontic optimization to appliance design and manufacturing. Detailed Description

[0094] In the following detailed description of the embodiments of the present disclosure, reference is made to the accompanying drawings, in which like reference numerals are assigned to like elements in the successive drawings. It should be noted that these drawings are provided to show the general functions and relationships according to the embodiments of the present invention, and are not intended to represent actual size or scale.

[0095] In use, the terms "first", "second", "third", etc. do not necessarily denote any order or priority relationship, but may be used to more clearly distinguish one element from another or time intervals.

[0096] In the context of the present disclosure, the term "image" refers to multi-dimensional image data composed of discrete image elements. For a 2D image, the discrete image elements are picture elements or pixels. For a 3D image, the discrete image elements are volumetric image elements or voxels. The term "volumetric image" is considered synonymous with the term "3D image".

[0097] In the context of the present disclosure, the term "code value" refers to the value associated with each 2D image pixel or, correspondingly, each volumetric image data element or voxel in the reconstructed 3D volumetric image. The code values of computed tomography (CT) or cone beam computed tomography (CBCT) images are typically but not always expressed in Hounsfield units that provide information about the attenuation coefficient of each voxel.

[0098] In the context of the present disclosure, the term "geometric primitive" relates to open or closed shapes such as rectangles, circles, lines, traced curves, or other traced patterns. The terms "landmark" and "anatomical feature" are considered equivalent and refer to specific patient anatomical structure features as shown.

[0099] In the context of the present disclosure, the terms "observer", "operator", and "user" are considered equivalent and refer to an observing practicing physician or other person who observes and manipulates images such as dental images on a display monitor. "Operator instructions" or "observer instructions" are obtained from explicit commands entered by an observer such as using a computer mouse, touch screen, or keyboard entry.

[0100] The term "highlight" for a displayed feature has its conventional meaning as understood by those skilled in the art of information and image display. Generally, highlighting uses some form of localized display enhancement to attract the attention of an observer. Highlighting, for example, a part of an image such as individual organs, bones, or structures, or a path from one chamber to another, can be achieved in any of a variety of ways, including but not limited to: annotation, displaying nearby or overlaid symbols, depicting contours or tracings, displaying with a color different from other image or information content, or with a significantly different intensity or gray-level value, making a part of the display blink or form an animation, or displaying with higher clarity or contrast.

[0101] In the context of the present disclosure, the descriptive term "derived parameter" relates to a value calculated based on the processing of acquired or entered data values. A derived parameter can be a scalar, point, line, volume, vector, plane, curve, angular value, image, closed contour, area, length, matrix, tensor, or mathematical expression.

[0102] As used herein, the term "set" refers to a non-empty set, as the concept of an aggregation of elements or members of a set is widely understood in elementary mathematics. Unless otherwise explicitly stated, the term "subset" is used herein to refer to a non-empty proper subset having one or more members, i.e., a subset of a larger set. For a set S, a subset can include the complete set S. However, a "proper subset" of a set S strictly speaking is contained within the set S and does not include at least one member of the set S. Alternatively, more formally, when using the term in the present disclosure, a subset B can be considered a proper subset of a set S when: (i) the subset B is non-empty; and (ii) the intersection B ∩ S is also non-empty and the subset B contains only elements in the set S and has a cardinality less than the cardinality of the set S.

[0103] In the context of the present disclosure, a "planar view" or "2D view" is a two-dimensional (2D) representation or projection of a three-dimensional (3D) object from a position on a horizontal plane through the object. This term is synonymous with the term "image slice" which is conventionally used to describe the display of a 2D planar representation from within 3D volumetric image data from a particular perspective. A 2D view of 3D volumetric data is considered to be substantially orthogonal when the corresponding planes at which the views are taken are set at 90 (+ / - 10) degrees relative to each other or are integer multiples of 90 degrees (n * 90 degrees, + / - 10 degrees) relative to each other.

[0104] In the context of the present disclosure, the general term "dentition element" relates to teeth, prosthetic devices such as dentures and implants, and support structures for teeth and associated prosthetic devices including the jaws.

[0105] The terms poly-curve and polycurve are equivalent and refer to a curve defined according to a polynomial.

[0106] The subject matter of the present disclosure relates to digital image processing and computer vision techniques, which can be understood to mean techniques for digitally processing data from digital images to identify objects, attributes or conditions understandable by humans and assign useful meanings thereto, and then utilizing the obtained results in further processing of the digital images.

[0107] As noted earlier in the background section, conventional 2D cephalometric analysis has several significant drawbacks. It is difficult to center the patient's head in a head holder or other measuring device, making reproducibility unlikely. The two-dimensional radiographs obtained produce overlapping images of the head anatomy rather than 3D images. Locating landmarks on a lateral cephalogram can be difficult and the results are often inconsistent (see the article by P. Planche and J. Treil entitled "Cephalometries for the next millennium" in The Future of Orthodontics, edited by Carine Carels, Guy Willems, Leuven University Press, 1998, pages 181 - 192). The task of developing and tracking treatment plans is complex, partly because of the large amount of cephalometric data that needs to be collected and computed.

[0108] Embodiments of the present disclosure utilize the theory of Treil in terms of selecting 3D anatomical landmark points, parameters derived from these landmark points, and the manner of using these derived parameters for cephalometric analysis. The reference publications created by Treil include "The Human Face as a 3D Model for Cephalometric Analysis" by Jacques Treil, B. Waysenson, J. Braga, and J. Casteigt in World Journal of Orthodontics, Supplement 2005, Vol. 6, No. 5, pp. 33-38; and "3D Tooth Modeling for Orthodontic Assessment" by J. Treil, J. Braga, J.-M. Loubes, E. Maza, J.-M. Inglese, J. Casteigt, and B. Waysenson in Seminars in Orthodontics, Vol. 15, p. 1, March 2009.

[0109] Figure 1 The schematic diagram of Figure 1 shows an imaging device 100 for 3D CBCT cephalometric imaging. To image a patient 12, a series of multiple 2D projection images are obtained and processed using the imaging device 100. A rotatable mount 130 is disposed on a column 118 and is preferably adjustable in height to accommodate the size of the patient 12. The mount 130 maintains an x-ray source 110 and a radiation sensor 121 on opposite sides of the head of the patient 12 and rotates to cause the source 110 and the sensor 121 to orbit around the head in a scanning pattern. The mount 130 rotates about an axis Q corresponding to the central portion of the patient's head such that the components attached to the mount 130 orbit around the head. The sensor 121 (a digital sensor) is coupled to the mount 130 opposite the x-ray source 110, and the x-ray source 110 emits a radiation pattern suitable for CBCT volumetric imaging. An optional head support 136 (such as a cheek rest or a bite element) stabilizes the patient's head during image acquisition. A computer 106 has an operator interface 104 and a display 108 for receiving operator commands and for displaying a volumetric image of the orthodontic image data obtained by the imaging device 100. The computer 106 communicates signals with the sensor 121 for obtaining image data and provides signals for controlling the source 110 and optionally for controlling a rotary actuator 112 for the components of the mount 130. The computer 106 also communicates signals with a memory 132 for storing the image data. An optional alignment device 140 is provided to assist in properly aligning the patient's head for the imaging process.

[0110] Reference Figure 2Logical flow diagram showing a sequence of steps 200 for obtaining orthodontic data for 3D cephalometric analysis using a dental CBCT volume, according to an embodiment of the present disclosure. In the data acquisition step S102, CBCT volume image data is accessed. The volume contains image data of one or more 2D images (or equivalently, slices). The original reconstructed CT volume is formed using a standard reconstruction algorithm from a plurality of 2D projections or sinograms obtained from a CT scanner. By way of example, Figure 3 shows an exemplary dental CBCT volume 202 that includes bony anatomy, soft tissue, and teeth.

[0111] Continuing Figure 2 the sequence, in the segmentation step S104, 3D dentition element data is collected by applying a 3D tooth segmentation algorithm to the dental CBCT volume 202. Segmentation algorithms for teeth and related dentition elements are well known in the field of dental imaging. Exemplary tooth segmentation algorithms are described, for example, in the following patents: U.S. Patent Application Publication No. 2013 / 0022252 to Chen et al., titled "PANORAMIC IMAGE GENERATION FROM CBCT DENTAL IMAGES"; U.S. Patent Application Publication No. 2013 / 0022255 to Chen et al., titled "METHOD AND SYSTEM FOR TOOTH SEGMENTATION IN DENTAL IMAGES"; and U.S. Patent Application Publication No. 2013 / 0022254 to Chen, titled "METHOD FOR TOOTH DISSECTION IN CBCT VOLUME", each of which is incorporated herein by reference in its entirety.

[0112] As Figure 4 shown, the tooth segmentation results are presented as an image 302, where the teeth are presented as a whole but are segmented individually. Each tooth is a separate entity called a tooth volume (e.g., tooth volume 304).

[0113] Each tooth in the segmented teeth, or more generally, each dentition element that has been segmented, has a 3D position list that includes at least the 3D position coordinates of each voxel within the segmented dentition element, as well as a list of code values for each voxel within the segmented element. At this point, the 3D position of each voxel is defined relative to the CBCT volume coordinate system.

[0114] In Figure 2 the reference marker selection step S106 in the sequence, the CBCT volume image is combined with two or more different 2D views obtained from different perspectives Figure 1Start display. Different 2D views can be at different angles and can be different image slices, or can be orthographic or substantially orthographic projections, or can be, for example, perspective views. According to an embodiment of the present disclosure, the three views are orthogonal to each other.

[0115] Figure 5 Illustrates an exemplary format in which the display interface 402 shows three orthogonal 2D views. In the display interface 402, the image 404 is one of the axial 2D views of the CBCT volume image 202 ( Figure 3 ). The image 406 is one of the coronal 2D views of the CBCT volume image 202, and the image 408 is one of the sagittal 2D views of the CBCT volume image 202. The display interface allows an observer such as a practicing doctor or technician to interact with a computer system that performs various image processing / computer algorithms in order to complete multiple 3D cephalometric analysis tasks. Observer interaction can take any of a variety of forms known to those skilled in the user interface art, such as using a pointer such as a computer mouse joystick or touch pad, or using a touch screen to select actions or specify coordinates of an image for interactions described in more detail subsequently.

[0116] One of the 3D cephalometric analysis tasks is to perform automatic identification in the Figure 2 3D reference marker selection step S106. The 3D reference markers, equivalent to a type of 3D landmark or feature point identified by an observer on the displayed image, are shown in different mutually orthogonal 2D views of the display interface 402 in Figure 5 . Figure 5 The exemplary 3D anatomical reference marker shown is the incisive foramen at reference marker 414. As shown in the view of Figure 6 , other anatomical reference markers that can be indicated by an observer on the displayed image 502 include the infraorbital foramina at reference markers 508 and 510 and the malleus at reference markers 504 and 506.

[0117] In Figure 2 step S106, the observer uses a pointing device (such as a mouse or touch screen) to place the reference marker as a type of geometric primitive at an appropriate position in any of the three views. According to an embodiment of the present disclosure shown in the accompanying drawings herein, the reference markers are shown as circles. Using, for example, Figure 5On the display interface screen, the observer places the small circle at position 414 in the view shown as image 404 as a reference marker for a reference point. The reference marker 414 is shown as a small circle in image 404 and is shown in the appropriate position in the corresponding views in images 406 and 408. Advantageously, it should be noted that the observer only needs to indicate the position of the reference marker 414 in any one of the displayed views 404, 406, or 408; the system responds by showing the same reference marker 414 in other views of the patient's anatomy. Thus, the observer can identify the reference marker 414 in the view where it is most easily visible.

[0118] After entering the reference marker 414, the user can use operator interface tools such as a keyboard or the displayed icons to adjust the position of the reference marker 414 on any of the displayed views. The observer also has the option to remove the entered reference marker and enter a new reference marker.

[0119] The display interface 402( Figure 5 ) provides a zoom in / zoom out utility for resizing any or all of the displayed views. The observer can thus effectively manipulate the different images to achieve improved reference marker positioning.

[0120] The aggregation of views of the reference 3D image content and the reference markers made and appearing on the views of the 3D image content provide a set of cephalometric parameters that can be used to more precisely characterize the shape and structure of the patient's head. The cephalometric parameters include coordinate information directly provided by the entry of reference markers for specific features of the patient's head. The cephalometric parameters also include information about various measurable characteristics of the anatomy of the patient's head, which is not entered directly as coordinates or geometric structures, but is derived from the coordinate information and is called "derived cephalometric parameters". The derived cephalometric parameters can provide information about relative size or volume, symmetry, orientation, shape, movement path and possible range of movement, inertia axis, centroid, and other data. In the context of the present disclosure, the term "cephalometric parameter" applies to those parameters directly identified by reference markers or those derived cephalometric parameters calculated based on reference markers. For example, when a specific reference point is identified by its corresponding reference marker, the framework connection line 522 is constructed to connect the reference points for proper characterization of the overall features, as shown more clearly in Figure 6 This is shown more clearly. The framework connection line 522 can be considered a vector in 3D space; its dimensional and spatial characteristics provide additional volumetric image data that can be used for orthodontic calculations and other purposes.

[0121] Each reference marker 414, 504, 506, 508, 510 is an end point of one or more framework connection lines 522 that are automatically generated by the computer 106 of the image processing device 100 within the volumetric data and form a framework that facilitates subsequent analysis and measurement processing. Figure 7A , Figure 7B and Figure 7C illustrates how the framework 520 of selected reference points (where the reference points are at vertices) for the displayed 3D images 502a, 502b, and 502c from different perspective views contributes to defining the dimensional aspects of the overall head structure. According to an embodiment of the present disclosure, operator instructions allow the operator to switch between 2D views similar to Figure 5 those shown and Figure 6 the volumetric representation shown, where the voxels of the patient's head have partial transparency. This enables the operator to examine the reference marker layout and the connection line layout from multiple angles; the adjustment of the reference marker positions can be made on any of the displayed views. Additionally, according to an embodiment of the present disclosure, the operator can type in more precise coordinates for a particular reference marker.

[0122] Figure 8 The logic flow diagram of Figure 2 illustrates the steps in a sequence for receiving and processing operator instructions for reference marker entry and identification and for providing parameters calculated based on the image data and reference markers. The display step S200 displays one or more 2D views from different angles (such as from mutually orthogonal angles) of the 3D image data reconstructed from a computed tomography scan of the patient's head. In the optional listing step S210, the system provides a text list such as a tabular list, a series of prompts, or a series of labeled fields for numeric entry, which requires the entry of position data for multiple landmarks or anatomical features in the reconstructed 3D image. This list can be explicitly provided to the operator in the form of user interface prompts or menu selections, as described subsequently. Alternatively, the list can be implicitly defined such that the operator does not need to follow a specific sequence for entering the position information. In the recording step S220, reference markers are entered that give the x, y, z position data of different anatomical features. The anatomical features can be located inside or outside the patient's mouth. Embodiments of the present disclosure can use a combination of the anatomical features identified on the display (as entered in step S220) and the segmentation data automatically generated for the teeth and other dentition elements (as previously referenced

[0123] In Figure 8In the recording step S220, the system receives an operator instruction for a reference marker corresponding to each landmark feature of the localization and anatomical structure. The reference marker is entered by the operator on either the first 2D view or the second 2D view, or on any of the other views in the case where more than two views are presented, and is displayed on each of the displayed views after being entered. The identification step S230 identifies the anatomical feature or landmark corresponding to the entered reference marker and optionally identifies the accuracy of the operator entry. A proportional value is calculated to determine the likelihood that the position of the reference marker entered by a given operator accurately identifies a specific anatomical feature. For example, the infraorbital foramen is typically within a certain distance range from the palatine foramen; the system checks the entered distance and notifies the operator in the case where the corresponding reference marker does not appear to be properly positioned.

[0124] Continue Figure 8 In the sequence of, in the construction step S240, a framework connection line is generated to connect the reference markers for framework generation. Then, the calculation and display step S250 is performed, which calculates one or more cephalometric parameters based on the located reference markers. Then, the calculated parameters are displayed to the operator.

[0125] Figure 9A , Figure 9B and Figure 9C shows the operator interface displayed on the display 108. The operator interface provides interactive utilities on the display 108 for receiving operator instructions and for displaying the calculation results of the cephalometric parameters of a specific patient. The display 108 can be, for example, a touch screen display for entering reference markers and other instructions specified by the operator. The display 108 simultaneously displays at least one 2D view of the volumetric image data from different angles or perspectives or two or more 2D views of the volumetric image data. For example, Figure 9A shows a frontal view or a coronal view 150, which is paired with a lateral view or a sagittal view 152. More than two views can be shown simultaneously and different 2D views can be shown, where each of the displayed views is independently positioned according to the embodiments of the present disclosure. The views can be orthogonal to each other or can simply be from different angles. As part of the interface of the display 108, an optional control 166 enables the observer to adjust the perspective angle from which one or more of the 2D views are obtained by switching between alternative fixed views or by incrementally changing the relative perspective angle along any of the 3D axes (x, y, z). Corresponding controls 166 can be provided for each 2D view Figure 1 as shown in FIGS. 9 to Figure 9C shown. Using the operator interface shown for the display 108, the operator enters each reference marker 414 using a certain type of pointer, which can be a mouse or other electronic pointer, or can be a touch screen entry, as Figure 9AAs shown. As part of the operator interface, the optional list 156 is set up to guide the operator to enter a specific reference marker according to a prompt, or to identify the operator's entry by, for example, selecting from a drop-down menu 168, as Figure 9B shown in the example. Thus, the operator can enter a value in list 156 or can enter a value in field 158, and then select a name associated with the entered value from the drop-down menu 168. Figures 9A to 9C Shows the framework 154 constructed between the reference points. As Figure 9A shown, each entered reference marker 414 can be shown in two views 150 and 152. The selected reference marker 414 is highlighted on the display 108, such as in bold or in another color. A specific reference marker is selected to obtain or enter information about the reference marker or to perform an action (such as moving its position).

[0126] In Figure 9B the embodiment shown, the reference marker 414 just entered or selected by the operator is identified by selecting from list 156. For the example shown, the operator selects the indicated reference marker 414 and then makes a menu selection, such as selecting "infraorbital foramen" from menu 168. The optional field 158 identifies the highlighted reference marker 414. For example, calculations based on models or known anatomical relationships based on standards can be used to identify the reference marker 414.

[0127] Figure 9C Shows an example where the operator enters an instruction for the reference marker 414 that is detected by the system as incorrect or impossible. An error prompt or error message 160 is displayed, indicating that the operator's entry appears to be incorrect. The system calculates the possible position of a particular landmark or anatomical feature, for example, based on a model or on learned data. When the operator's entry appears to be inaccurate, the message 160 is displayed along with an optional alternative position 416. An override instruction 162 is displayed along with a repositioning instruction 164 for repositioning the reference marker according to the calculated information from the system. Repositioning can be done by accepting another operator entry from the display or keyboard or by accepting the reference marker position calculated by the system (in Figure 9C the example, at the alternative position 416).

[0128] According to an alternative embodiment of the present disclosure, the operator does not need to label the reference marker when entering it. Instead, the display prompts the operator to indicate a particular landmark or anatomical feature on any of the displayed 2D views and automatically labels the indicated feature. In this guided sequence, the operator responds to each system prompt by indicating the position of the corresponding reference marker for the specified landmark.

[0129] According to another alternative embodiment of the present disclosure, the system determines which landmark or anatomical feature has been identified when the operator indicates a reference marker; the operator does not need to label the reference marker when entering it. The system uses the known information about the identified anatomical feature and optionally calculates the most likely reference marker by using the dimensions of the reconstructed 3D image itself for the calculation.

[0130] Using Figures 9A to 9C The operator interface as shown in the example of, embodiments of the present disclosure provide a practical 3D cephalometric analysis system that synergistically combines the skills of a human operator of the system with the capabilities of a computer during the process of 3D cephalometric analysis. This utilizes human creativity, heuristic use, flexibility, and judgment and combines these with computer advantages such as computational speed, the ability to process accurately and repeatedly, reporting and data access and storage capabilities, and display flexibility.

[0131] Return reference Figure 2 Once a sufficient set of landmarks has been entered, the derived cephalometric parameters are calculated in the calculation step S108. Figures 10A to 10E The processing sequence for calculating and analyzing cephalometric data is shown, and it is shown how multiple cephalometric parameters are obtained from the combined volumetric image data and anatomical feature information according to the instructions entered by the operator and according to the segmentation of the dentition elements. According to an embodiment of the present disclosure, Figures 10A to 10E A portion of the feature as shown is displayed on the display 108( Figure 1 ).

[0132] Figure 10A The exemplary derived cephalometric parameters shown are a 3D plane 602 (called the t-reference plane in cephalometric analysis) calculated by using a subset of a set of first geometric primitives having reference markers 504, 506, 508, and 510 as described in the previous reference Figure 6 . Another derived cephalometric parameter is a 3D coordinate reference system 612, called the t-reference system and described by Treil in the previously cited publication. The z-axis of the t-reference system 612 is selected to be perpendicular to the 3D t-reference plane 602. The y-axis of the t-reference system 612 is aligned with the framework connection line 522 between the reference markers 508 and 504. The x-axis of the t-reference system 612 is in the plane 602 and is orthogonal to both the z-axis and the x-axis of the t-reference system. The directions of the t-reference system axes are in Figure 10A and in the subsequent Figure 10B , Figure 10C , Figure 10D and Figure 10E as indicated. The origin of the t-reference system is at the middle of the framework connection line 522 connecting the reference markers 504 and 506.

[0133] In the case of establishing the t reference system 612, the 3D reference markers from step S106 and the 3D tooth data (list of 3D positions of teeth) from step S104 are transformed from the CBCT volume coordinate system to the t reference system 612. In the case of performing this transformation, subsequent calculations and analyses for deriving cephalometric parameters can now be performed with respect to the t reference system 612.

[0134] Reference Figure 10B , the 3D upper plane 704 and the 3D lower plane 702 can be derived from the cephalometric parameters of the tooth data in the t reference system 612. The upper plane 704 is derived based on the tooth data segmented from the upper jaw (maxilla). The lower plane 702 is similarly derived based on the tooth data segmented from the lower jaw (mandible) using methods familiar to those skilled in the art of cephalometric measurement and analysis.

[0135] For an exemplary calculation of the 3D plane based on the tooth data, an inertia tensor is formed by using the 3D position vectors and code values of the voxels of all the teeth in the jaw (as described in the publication pointed out by Treil); then, the eigenvectors are calculated based on the inertia tensor. These eigenvectors mathematically describe the orientation of the jaw in the t reference system 612. Two of the eigenvectors or one of the eigenvectors can be used as the plane normal to form the 3D plane.

[0136] Reference Figure 10C , showing other derived parameters. For each jaw, a jaw curve is calculated as a derived parameter. The upper jaw curve 810 is calculated for the upper jaw; the lower jaw curve 812 is derived for the lower jaw. The jaw curves are configured to intersect the centroid of each tooth in the corresponding jaw and lie in the corresponding jaw plane. Subsequently, the 3D position list and the code value list of the segmented teeth can be used to calculate the centroid of the teeth.

[0137] The mass of the teeth is also a derived cephalometric parameter calculated based on the list of code values of the teeth. In Figure 10C , for the upper jaw teeth, an exemplary tooth mass is shown as a circle 814 or other type of shape. According to the embodiments of the present disclosure, one or more of the relative dimensions of the shape (such as the radius of the circle) indicate the relative mass value, that is, the mass value of a specific tooth relative to the mass of other teeth in the jaw. For example, the first molar of the upper jaw has a mass value greater than the mass values of the adjacent teeth.

[0138] According to the embodiments of the present disclosure, an eigenvector system is also calculated for each tooth. Initially, an inertia tensor is formed by using the 3D position vectors and code values of the voxels of the tooth, as described in the publication pointed out by Treil. Then, the eigenvectors are calculated as derived cephalometric parameters based on the inertia tensor. These eigenvectors mathematically describe the orientation of the tooth in the t reference system.

[0139] As Figure 10D shown, another derived parameter, i.e., the occlusal plane (3D plane 908), is calculated based on two jaw planes 702 and 704. The occlusal plane (3D plane 908) is located between the two jaw planes 702 and 704. The normal of plane 908 is the average of the normals of plane 702 and plane 704.

[0140] For each tooth, generally, the eigenvector corresponding to the largest calculated eigenvalue is another derived cephalometric parameter indicating the long axis of the tooth. Figure 10E Exemplary long axes of two types of teeth are shown: the long axis 1006 of the upper incisor and the long axis 1004 of the lower incisor.

[0141] The calculated length of the long axis of the tooth, along with other derived parameters, is a useful cephalometric parameter in cephalometric analysis and treatment planning. It should be noted that instead of using eigenvalues to set the length of the axis as proposed by Triel in the cited publication, the embodiments of the present disclosure use a different method to calculate the actual long axis length as a derived parameter. Initially, the first intersection point of the long axis and the bottom slice of the tooth volume is located. Then, the second intersection point of the long axis and the top slice of the tooth volume is identified. The embodiments of the present disclosure then calculate the length between the two intersection points.

[0142] Figure 11 A chart 1102 is shown, which provides a close-up view isolating the occlusal plane 908 relative to the upper jaw plane 704 and the lower jaw plane 702 and showing the relative positions and curvatures of the jaw curves 810 and 812.

[0143] Figure 12 A chart 1202 is shown, which shows the positional and angular relationship between the upper tooth long axis 1006 and the lower tooth long axis 1004.

[0144] As pointed out in the foregoing description and shown in the corresponding drawings, there are a plurality of cephalometric parameters that can be derived from the combined volumetric image data (including dentition element segmentation and operator-entered reference markers). These parameters are calculated in the computer-aided cephalometric analysis step S110 ( Figure 2 ).

[0145] One exemplary 3D cephalometric analysis procedure that can be particularly valuable in step S110 relates to the relative parallelism of the maxillary (upper jaw) plane 702 and the mandibular (lower jaw) plane 704.. Both the upper jaw plane 702 and the lower jaw plane 704 are derived parameters, as previously pointed out. The evaluation can be performed using the following sequence:

[0146] · Project the x-axis of the maxillary inertial system (i.e., the eigenvector) onto the x-z plane of the t reference system and calculate the angle MX1_RF between the z-axis of the t reference system and the projection;

[0147] · Project the x-axis of the mandibular inertial system (i.e., the eigenvector) onto the x-z plane of the t reference system and calculate the angle MD1_RF between the z-axis of the t reference system and the projection.

[0148] · MX1_MD1_RF = MX1_RF - MD1_RF gives an evaluation of the parallelism between the upper jaw and the lower jaw in the x-z plane of the t reference system.

[0149] · Project the y-axis of the maxillary inertial system (i.e., the eigenvector) onto the y-z plane of the t reference system and calculate the angle MX2_RS between the y-axis of the t reference system and the projection.

[0150] · Project the y-axis of the mandibular inertial system (i.e., the eigenvector) onto the y-z plane of the t reference system and calculate the angle MD2_RS between the y-axis of the t reference system and the projection.

[0151] · MX2_MD2_RS = MX2_RS - MD2_RS gives an evaluation of the parallelism between the upper jaw and the lower jaw in the y-z plane of the t reference system.

[0152] Another exemplary 3D cephalometric analysis procedure performed in step S110 is to use the central axes 1006 and 1004 ( Figure 10E 、 Figure 12 ) to evaluate the angular characteristics between the maxillary (upper jaw) incisors and the mandibular (lower jaw) incisors. The evaluation can be performed using the following sequence:

[0153] · Project the central axis 1006 of the upper incisors onto the x-z plane of the t reference system and calculate the angle MX1_AF between the z-axis of the t reference system and the projection.

[0154] · Project the central axis 1004 of the lower incisors onto the x-z plane of the t reference system and calculate the angle MD1_AF between the z-axis of the t reference system and the projection.

[0155] · MX1_MD1_AF = MX1_AF - MD1_AF gives an evaluation of the angular characteristics between the upper incisors and the lower incisors in the x-z plane of the t reference system.

[0156] · Project the central axis 1006 of the upper incisors onto the y-z plane of the t reference system and calculate the angle MX2_AS between the y-axis of the t reference system and the projection.

[0157] · Project the central axis 1004 of the lower incisors onto the y-z plane of the t reference system and calculate the angle MD2_AS between the y-axis of the t reference system and the projection.

[0158] · MX2_MD2_AS = MX2_AS - MD2_AS gives an evaluation of the angular characteristics between the upper incisors and the lower incisors in the y-z plane of the t reference system.

[0159] Figure 13 Figure 1300 is shown, which shows a local x-y-z coordinate system 1302 for the upper incisors and a local x-y-z coordinate system 1304 for the lower incisors. The local axes of the x-y-z coordinate system are aligned with the eigenvectors associated with that particular tooth. The x-axis is not shown but satisfies the right-hand rule.

[0160] In Figure 13 , the origin of system 1302 can be chosen to be anywhere along axis 1006. An exemplary origin of system 1302 is the centroid of the tooth associated with axis 1006. Similarly, the origin of system 1304 can be chosen to be anywhere along axis 1004. An exemplary origin of system 1304 is the centroid of the tooth associated with axis 1004.

[0161] Based on the analysis performed in step S110 ( Figure 2 ), an adjustment or treatment plan is arranged in planning step S112. An exemplary treatment plan is to rotate the upper incisors counterclockwise at a 3D point (such as at the origin of its local coordinate system) and about an arbitrary 3D axis (such as about the x-axis of the local x-y-z system). Figure 14 The figure of

[0162] In Figure 2 the treatment step S114 of

[0163] Returning to reference Figure 2 , line 120 from step S114 to step S102 is shown. This indicates the presence of a feedback loop in the sequence 200 workflow. After the patient has undergone treatment, an immediate assessment of the treatment can be performed or alternatively a scheduled assessment can be made by entering relevant data as input to the system. Exemplary relevant data for this purpose can include results from optical, radiographic, MRI, or ultrasound imaging and / or any meaningful relevant measurements or results.

[0164] In Figure 2 sequence 200 of Figure 15The figure shows how the system can use a virtual or digital dental model 912 to learn tooth extraction. The digital dental model 912 is a virtual model for calculation and display constructed using a set of landmarks and a set of upper teeth of a digital model of the upper jaw and a set of lower teeth of a digital model of the lower jaw. The digital dental model 912 is a 3D or volumetric image data model representing image data obtained from a patient's anatomy and generated using landmarks and other anatomical information provided, and can be stored for reference or generated as needed for use. The use of various types of digital dental models is well known to those skilled in the field of digital radiography. The landmarks of the digital dental model 912 such as reference markers 504, 506, 508, and 510 correspond to the actual reference markers identified from the CBCT volume 202 ( Figure 3 [[ID=**2**]]) These landmarks are used to calculate the t-reference frame 612 ( Figures 10A to 10E ).

[0165] The operator can extract one or more teeth by selecting the teeth from the display or by entering information identifying the teeth to be extracted on the display.

[0166] In Figure 15 representation, the upper and lower teeth such as the digital teeth 2202 and 2204 of the digital dental model 912 are digitally generated. The exemplary shape of the digital teeth is a cylinder, as shown. In this example, the exemplary voxel value of the digital teeth is 255. It can be understood that other shapes and values can be used for the representation and processing of the dental model 912.

[0167] Figure 16A Shows the digital teeth 2202 and 2204 of the digital dental model 912. The corresponding digital teeth in the upper digital jaw and the lower digital jaw are generated in the same way, having the same size and the same code value.

[0168] To evaluate the parallelism of the upper and lower digital jaws, the inertia tensor of each digital jaw is formed by using the 3D position vectors and code values of the voxels of all the digital teeth in the digital jaw (see the previously cited Treil publication). Then, the eigenvectors are calculated based on the inertia tensor. These 5 eigenvectors mathematically describe the orientation of the jaw in the t-reference frame 612 ( Figure 10A ). As pointed out earlier, the eigenvectors calculated based on the inertia tensor data are a type of derived cephalometric parameter.

[0169] As Figure 16B shown, since the upper and lower jaw teeth are created in the same way, as expected, for the generated digital dental model 912, the calculation axes of the upper digital jaw inertial frame 2206 and the lower digital jaw inertial frame 2208 are parallel. Figure 17A Shows this parallelism along the line 2210 for the upper jaw and along the line 2212 for the lower jaw in the sagittal view;Figure 17B Shows the parallelism at line 2214 for the upper jaw and at line 2216 for the lower jaw in the frontal (coronal) view.

[0170] Reference Figure 18A and Figure 18B , shows the case where the digital tooth 2204 is missing. The calculation axes of the upper digital jaw inertial system 2206 and the lower digital jaw inertial system 2208 are no longer parallel. In the corresponding Figure 19A and Figure 19B , this misalignment can also be checked in the sagittal view along line 2210 for the upper jaw and line 2212 for the lower jaw; in the frontal view along line 2214 for the upper jaw and line 2216 for the lower jaw. According to an embodiment of the present disclosure, this type of misalignment of the upper jaw plane and the lower jaw plane (inertial system) caused by one or more missing teeth can be corrected by removing the companion teeth of each missing tooth, as shown in Figure 20A and Figure 20B . The companion teeth of tooth 2204 are teeth 2304, 2302, and 2202. Tooth 2304 is the corresponding tooth of tooth 2204 in the upper jaw. Teeth 2202 and 2302 are the corresponding teeth of teeth 2304 and 2204 on the other side. After removing the companion teeth of the missing tooth 2204, the calculation axes of the inertial system 2206 for the upper jaw and the inertial system 2208 for the lower jaw return to parallel.

[0171] Figure 21A and Figure 21B Show the segmented teeth of the CBCT volume in the case of removing the companion teeth of the missing tooth. The segmentation result is shown in image 2402. The calculation axes of the inertial systems for the upper jaw and the lower jaw are parallel, as shown in chart 2404.

[0172] Figure 22A and Figure 22B Show the companion tooth removal method applicable to another patient using the tooth removal step S124 ( Figure 2 ). As shown in image 2500, teeth 2502, 2504, 2506, and 2508 are not fully developed. According to the inertial system calculation, their positioning, size, and orientation seriously distort the physical properties of the upper jaw and the lower jaw. Figure 22B The chart 2510 in

[0173] Figure 23A and Figure 23B Show the result of removing specific teeth from the image. Image 2600 shows the result of removing from Figure 22AThe result of removing teeth 2502, 2504, 2506, and 2508 from image 2500. In the absence of the disruption of these teeth, the axes of the maxillary inertial system 2612 and the mandibular inertial system 2614 of the teeth shown in image 2600 are parallel, as depicted in chart 2610.

[0174] Biometric calculation

[0175] Given the entry landmark data of the anatomical reference points, the segmentation of the dentition elements (such as teeth, implants, and jaws and related supporting structures), and the calculated parameters obtained as previously described, detailed biometric calculations can be performed and their results can be used to assist in setting the treatment plan and monitoring the ongoing treatment process. Return reference Figure 8 , and the subsequent described biometric calculations give more details about step S250 for analyzing and displaying the parameters generated based on the recorded reference markers.

[0176] According to an embodiment of the present disclosure, the entry landmarks and the calculated inertial system of the teeth are transformed from the original CBCT image voxel space to an alternative reference system called the direct orthogonal landmark (DOL) reference system, where the coordinates are (x d , y d , z d ). Figure 24 Shows multiple landmarks and coordinate axes or vectors of the DOL reference system. Landmarks RIO and LIO indicate the infraorbital foramen; landmarks RHM and LHM mark the malleus. The origin o d , y d , z d ) of (x d ) is selected to be at the middle of the line connecting landmarks RIO and LIO. The direction of vector x d is defined as from landmark RIO to LIO. The YZ plane is orthogonal to vector x d at point o d . The plane YZ intersects the line connecting RHM and LHM at point o' d . The direction of vector y d is from o'd to o d . Vector z d is the cross product of x d and y d .

[0177] Using this transformation, the identified landmarks can be remapped to the Figure 25 shown coordinate space. Figure 26 Shows an example of the inertial system with the remapping transformation from a side view.

[0178] By way of example and not limitation, the following list identifies a number of individual data parameters that may be calculated using transformed landmarks, dentition segmentation, and inertial frame data and used for further analysis.

[0179] The first group of data parameters that can be calculated using the flags in the transform space gives the before and after values:

[0180] 1. Anteroposterior. Alveolar. GIM-Gim: The y-position difference between the mean center of inertia of the upper and lower incisors.

[0181] 2. Front and rear. Tooth groove. GM-Gm: The difference between the mean center of inertia of the upper and lower teeth.

[0182] 3.Anterior-posterior.Alveolar.TqIM: average torque of the upper incisor.

[0183] 4.Anterior-posterior.Alveolar.Tqim: Average torque of the lower incisor.

[0184] 5. Anterior and posterior cogs. (GIM + Gim) / 2: Average y position of GIM and Gim.

[0185] 6.Anterior-posterior.Basal.MNP-MM: The y-position difference between the mean nasopalatine foramen and the mean mental foramen.

[0186] 7.Anterior-posterior.Base.MFM-MM: The actual distance between the mean mandibular foramen and the mean mental foramen.

[0187] 8.Anterior-posterior.Architecture.MMy: Mean mental foramen y position.

[0188] 9. Anteroposterior. Architecture. MHM-MM: Actual distance between the mean malleus and the mean mental foramen.

[0189] The second grouping gives the vertical values:

[0190] 10. Vertical. Alveolar. Gdz: The z position of the center of inertia of all teeth.

[0191] 11. Vertical. Alveolar. MxII-MdII: The difference between the angles of the secondary axes of the upper and lower dental arches.

[0192] 12. Vertical. Base.<MHM-MIO,MFM-MM> : The angle difference between vectors MHM-MIO and MFM-MM.

[0193] 13.Vertical.Frame.MMz: Mean mental foramen z position.

[0194] 14. Vertical. Architecture. 13: Angular difference between vectors MHM-MIO and MHM-MM.

[0195] A horizontal value is also provided:

[0196] 15. Transverse. Alveolar. dM - dm: The difference between the upper right / left molar distance and the lower right / left molar distance.

[0197] 16. Transverse. Alveolar. TqM - Tqm: The difference between the torques of the upper first and second molars and the torques of the lower first and second molars.

[0198] 17. Transverse. Basal. (RGP - LGP) / (RFM - LFM): The ratio of the right / left greater palatine foramen distance to the mandibular foramen distance.

[0199] 18. Transverse. Framework. (RIO - LIO) / (RM - LM): The ratio of the right / left infraorbital foramen to the mental foramen distance.

[0200] The following gives other calculated or "derived" values:

[0201] 19. Derived. Hidden. GIM: The average upper incisor y - position.

[0202] 20. Derived. Hidden. Gim: The average lower incisor y - position.

[0203] 21. Derived. Hidden. (TqIM + Tqim) / 2: The average of the average torque of the upper incisors and the average torque of the lower incisors.

[0204] 22. Derived. Hidden. TqIM - Tqim: The difference between the average torque of the upper incisors and the average torque of the lower incisors.

[0205] 23. Derived. Hidden. MNPy: The average nasopalatine y - position.

[0206] 24. Derived. Hidden. GIM - MNP(y): The difference between the average upper incisor y - position and the average nasopalatine y - position.

[0207] 25. Derived. Hidden. Gim - MM(y): The average mental foramen y - position.

[0208] 26. Derived. Hidden. Gdz / (MMz - Gdz): The ratio between the value of Gdz and the value of MMz - Gdz.

[0209] It should be noted that this list is exemplary and can be enlarged, edited, or changed in some other way within the scope of the present disclosure.

[0210] In the exemplary list given above, there are 9 parameters in the anterior - posterior classification, 5 parameters in the vertical classification, and 4 parameters in the transverse classification. Each of the above - mentioned classifications in turn has three types: alveolar, basal, and framework. Additionally, there are 8 derived parameters that may not represent a specific spatial position or relationship but are used in subsequent calculations. These parameters can be further labeled as normal or abnormal.

[0211] The normal parameter has a positive relationship with the anteroposterior discrepancy, that is, in terms of its value:

[0212] Class III < Class I < Class II.

[0213] Among them, the Class I value indicates the normal relationship between the upper teeth, lower teeth and the jaw or the balanced occlusal part; the Class II value indicates that the lower first molar is posterior relative to the upper first molar; the Class III value indicates that the lower first molar is anterior relative to the upper first molar.

[0214] The abnormal parameter has a negative relationship with the anteroposterior discrepancy, that is, in terms of its occlusion-related value:

[0215] Class II < Class I < Class III.

[0216] Embodiments of the present disclosure may use an analysis engine to calculate a set of possible conditions that can be used to interpret and as a guide for a treatment plan. Figures 27 to 38 Shows various aspects of the operation and organization of the analysis engine and some of the text, tabular results, and graphical results generated by the analysis engine. It should be noted that a computer, workstation, or host processor can be configured as an analysis engine according to a set of pre-programmed instructions for completing the necessary tasks and functions.

[0217] [[ID=2,2]]According to an embodiment of the present disclosure, the analysis engine can be modeled as a three-layer network 2700, as Figure 27 shown. In this model, the row and column node inputs can be considered as a set of comparators 2702 that are directed to provide binary outputs based on the row and column input signals. One output cell 2704 is activated for each set of possible input conditions, as shown. In the example shown, the input layer 1 2710 is filled with one of the previously listed 26 parameters, and the input layer 2 2720 is filled with another of the 26 parameters. The output layer 2730 contains 9 cells, and each of the 9 cells represents a possible analysis when the two inputs meet certain criteria, that is, when the values of the two inputs are within a specific range.

[0218] According to an embodiment of the present disclosure, the analysis engine has thirteen networks. These networks include independent networks similar to Figure 27 the network shown and coupled networks 2800 and 2810 as Figure 28 shown.

[0219] Figure 29 The algorithm shown describes the operation of an independent analysis network (such as the independent analysis network shown in the instance of Figure 27 ). Here, the values x and y are the input parameter values; m represents the network index; D(i,j) is the output cell. The "estimation vector c m " of the column value and the "estimation vector rm Steps of " " are checked to determine what measurement criteria the input values satisfy. For example, in the following formula, if then c m = [true, false, false].

[0220] Figure 28 The coupling network of " " combines the results from two other networks and can operate as described in the algorithm of Figure 30 . Similarly, the values x and y are input values; m represents the network index; D(i,j) is the output cell. The "measurement vector c k " of the column values and the "measurement vector r k " of the row values are checked in steps to determine what measurement criteria the input values satisfy.

[0221] In a broader aspect, the overall network arrangement using the independent network model described in reference Figure 27 or the coupled network model described in reference Figure 28 allows for analysis to review, compare, and combine various metrics in order to provide useful results that can be reported to a practicing physician and used for treatment planning.

[0222] Figure 31A Exemplary parameters for the main tooth malocclusions relative to teeth for a specific patient are listed as numerical values and their interpretations, and the exemplary parameters are based on the list of 26 parameters given previously. Figure 31B , Figure 31C and Figure 31D Exemplary parameters for the maxillofacial asymmetry relative to a specific patient are listed as numerical values and their interpretations, and the exemplary parameters are based on the list of a total of 63 parameters given in the exemplary embodiments of the present application. Figure 32A Exemplary tabulation result 3200 showing a specific example with occlusal analysis and arch angle characteristics is shown. In the Figure 32A example, the columns indicate open bite, normal incisor relationship, or overbite conditions. The rows represent the occlusion class and arch angle conditions. As Figure 32A shown, highlighting can be used to emphasize the display of information about abnormal conditions or other conditions of particular interest. For the Figure 32A specific patient in the example, the analysis indicates an open bite condition with Class III occlusion characteristics as a result. This result can be used to develop a treatment plan based on severity and the judgment of the practicing physician.

[0223] Figure 32B Exemplary tabulation result 3200 showing another example of the analysis of the torque of the upper and lower incisors is shown, and the analysis uses parameters 3 and 4 from the list given previously.

[0224] Figure 32CExemplary tabulation result 3200 showing another example of the evaluation of double retrusion or double protrusion, the evaluation using the calculation parameters given earlier as parameters (5) and (21).

[0225] Figure 32D An exemplary summary list showing the results of a cephalometric analysis of a particular patient. The list shown refers to the analysis indications obtained with respect to the previously listed parameters 1 - 26. In Figure 32D a particular instance, there are 13 results of parameter comparisons using biometric parameters and dentition information derived as described herein. Additional or fewer results may be provided in practice. Figure 32E A detailed list showing one of the conditions reported in a tabulation list having a table 3292 including a cell 3294, as shown subsequently ( Figure 35 ).

[0226] The result information from biometric calculations can be provided to practicing physicians in a variety of different formats. Tabular information (such as Figures 31A to 32E the tabular information shown) can be provided in a file form (such as in comma - separated value (CSV) form compatible with display and further calculations) in a tabular spreadsheet arrangement, or can be provided in other forms (such as by providing a text message). A graphical display (such as Figure 26 the graphical display described) can alternatively be provided as an output, where specific results are highlighted, such as by the intensity or color of the display of features, where measured and calculated parameters show abnormal biometric relationships, such as overjet, underjet, and other conditions.

[0227] Calculated biometric parameters can be used in an analysis sequence where related parameters are processed combinatorially to provide results that can be compared with statistical information collected from a patient population. Then, the comparison can be used to indicate abnormal relationships between various features. This relationship information can help show how different parameters affect each other in the case of a particular patient and can provide resulting information for guiding treatment planning.

[0228] Returning to reference Figure 1 , the memory 132 can be used to store a statistical database of cephalometric information collected from a patient population. Various items of biometric data providing dimensional information about teeth and related supporting structures, as well as additional information about occlusion, dentition, and the interrelationships of the head portion and the mouth based on this data, can be stored and analyzed according to the patient population. The analysis results themselves can be stored, thus providing a database of predetermined values that can yield a significant amount of useful information for treating individual patients. According to an embodiment of the present disclosure, for each patient, calculations are made and stored, and can be stored for hundreds of patients or for at least a statistically significant group of patients Figure 31A and Figure 31BThe parameter data listed in . The stored information includes information that can be used to determine ranges that are considered normal or abnormal and require correction. Then, in the case of an individual patient, comparison between the biometric data from the patient and the stored values calculated based on the database can help provide guidance for an effective treatment plan.

[0229] As is well known to those skilled in the art of orthodontics and related fields, the relationships between various biometric parameters measured and calculated for various patients can be complex, such that multiple variables must be calculated and compared in order to appropriately assess the need for corrective action. Relative to Figure 27 and Figure 28 The analysis engine described in simple form compares different parameter pairs and provides a series of binary output values. However, in practice, more complex processing can be performed, taking into account the range of conditions and values seen in the patient population.

[0230] Highlighting specific measured or calculated biometric parameters and results provides useful data that can guide the treatment plan for a patient.

[0231] Figure 33 A system display showing result 3200 with a recommended message 170 based on the analysis result and highlighting features of the patient's anatomy related to the recommendation. Figure 34 A system display 108 showing a graphical depiction of analysis result 3200. Annotated 3D views (e.g., 308a - 308d) arranged at different angles are shown along with recommended message 170 and controls 166.

[0232] Certain exemplary method and / or apparatus embodiments according to the present disclosure can address the need for objective metrics and displayed data that can be used to assist in gauging asymmetrical facial / dental anatomy. Advantageously, the exemplary method and / or apparatus embodiments present measurement and analysis results displayed in multiple formats suitable for evaluation by a practicing physician.

[0233] Figure 35 An exemplary text report of maxillofacial asymmetry assessment according to an embodiment of the present disclosure is shown. The report lists a set of assessment tables (T1 - T19) obtainable from the system, where cell entries (indicated by C (i.e., C(row, column)) with row and column indices) provide an assessment opinion of maxillofacial / dental structural asymmetry characteristics of the calculated tissue based on the relationship with the obtained parameters such as Figure 31B the parameters P1 - P15 in . Figure 32E An exemplary assessment table 3292 with four rows and four columns is depicted in .

[0234] In one embodiment, for each exemplary evaluation table (e.g., 19 evaluation tables), only one cell 3294 can be activated at a time; the content of the activated cell is highlighted, such as by displaying it in red font. In the exemplary table 3292, the activated cell is C(2,2)(3294), where the content "0" indicates that no asymmetry was found for the characteristics of the incisor and molar upper / lower deviation.

[0235] For quick reference to the exemplary evaluation tables, the system of the present disclosure generates a concise summary page of the checklist type that provides information about the table number (Tn), parameter number (Pk,j), cell index (Cs,t), and the actual evaluation opinions from the evaluation tables T1 - T19 (e.g., Figure 35 ). The information obtained from this type of text report can assist the practicing physician in providing at least some objective metrics that can be used to develop a treatment plan or estimate the treatment process for a specific patient. Other benefits to the practicing physician can be cumulative summary estimates related to the overall condition assessment of the patient. This can be particularly the case when determining the multiple conditional reference points of the patient's asymmetric facial / dental anatomy or relationships and the relationships between them involve a large number of view-oriented and 3D orientation treatment conditions and variable root causes.

[0236] In one exemplary asymmetric determination table embodiment, the 19 evaluation tables can include hundreds of reference points and hundreds of relationships between them. In this exemplary asymmetric determination table embodiment, the tables include:

[0237] T1: Asymmetric matching of incisor and molar upper / lower deviation;

[0238] T2: Dental arch rotation;

[0239] T3: Right rotation of the upper / lower dental arch and reactivity of the upper or lower dental arch;

[0240] T4: Asymmetric matching of incisor upper / lower deviation and upper incisor transverse deviation, reaction of the upper or lower dental arch in the upper / lower incisor transverse deviation;

[0241] T5: Asymmetric matching of incisor upper / lower deviation and anterior base transverse deviation, reaction of the upper or lower dental arch anterior deviation in the upper / lower incisor transverse deviation;

[0242] T6: Asymmetric matching of incisor upper / lower molar deviation and upper molar transverse deviation, reaction of the upper or lower molar transverse deviation;

[0243] T7: Asymmetric matching of incisor upper / lower molar deviation and lower molar transverse deviation;

[0244] T8: Asymmetric matching of basal bone upper / lower deviation;

[0245] T9: Asymmetrically matched basal bone upper / lower anterior relationships and maxillary anterior deviation;

[0246] T10: Asymmetrically matched basal bone upper / lower anterior relationships and mandibular anterior deviation;

[0247] T11: Asymmetrically matched incisor upper / lower deviation and anterior basal transverse deviation;

[0248] T12: Vertically asymmetric comparison of L / R molar height difference and maxillary dental arch roll;

[0249] T13: Asymmetric comparison of L / R molar height difference and mandibular dental arch roll;

[0250] T14: Vertically asymmetric comparison of basal bone R / L posterior difference (maxilla and mandible);

[0251] T15: Vertically asymmetric comparison of L / R difference at pogonion level (measuring maxillofacial region and overall face);

[0252] T16: Anteroposteriorly asymmetric comparison of R / L upper / lower molar anteroposterior difference and the latter;

[0253] T17: Anteroposteriorly asymmetric comparison of R / L upper / lower molar anteroposterior relationship difference and the latter;

[0254] T18: Anteroposteriorly asymmetric comparison of R / L upper basal lateral landmark anteroposterior difference and the latter;

[0255] T19: Anteroposteriorly asymmetrically matched mandibular ramus and R / L overall hemifaces.

[0256] In the determination of such complex asymmetric facial / dental anatomical structures or relationships according to the present application, optionally cumulative summary measures related to the overall condition assessment of the patient are preferably used. In some embodiments, exemplary cumulative summary or overall diagnostic opinions may include: anteroposterior direction of asymmetry (AP opinion or S1), vertical direction of asymmetry (VT opinion or S2), and transverse direction of asymmetry (TRANS opinion or S3). Further still, one or more highest scores can be used to determine the overall asymmetry score (overall asymmetry determination) by using one or more of the measures or by combining S1, S2, and S3. For example, an exemplary overall asymmetry score can be a summary (e.g., overall Class I, II, III), which is divided into several limited classifications (e.g., normal, limited measure, recommended detailed assessment) or is represented / characterized by the major asymmetry conditions (e.g., S1, S2, S3).

[0257] As Figure 35 shown, the exemplary text report also presents the S1 anteroposterior direction "comprehensive" asymmetry opinion, the S2 vertical direction comprehensive asymmetry opinion, and the S3 transverse direction comprehensive asymmetry opinion.

[0258] The term "synthesis" is derived in this application to form a pair of tables in each direction. In some exemplary embodiments, the term "synthesis" may be determined based on a combination of multiple tables from each evaluation type (e.g., AP, V, Trans that involve or represent a substantial (e.g., >50%) portion of the skull) or a pair of tables in each direction.

[0259] For example, the S1 synthesis opinion is derived from Tables 17 and 19. The derivation first assigns scores to each cell in Tables 17 and 19. An exemplary score assignment is explained as follows:

[0260] For Table 17, C(1,3) = -2; C(1,2) = C(2,3) = -1; C(2,1) = C(3,2) = 1; C(3,1) = 2; and other cells are assigned a value of 0.

[0261] For Table 19, C(1,1) = -2; C(1,2) = C(2,1) = -1; C(2,3) = C(3,2) = 1; C(3,3) = 2; and other cells are assigned a value of 0.

[0262] The derivation of the S1 synthesis opinion estimates the combined score by adding the scores from Tables 17 and 19.

[0263] For example, if C(1,3) in Table 17 is activated and C(1,1) in Table 19 is activated, the combined score will be the sum of the scores of C(1,3) in Table 17 and C(1,1) in Table 19. Since C(1,3) in Table 17 is assigned a value of -2 and C(1,1) in Table 19 is assigned a value of -2, the combined score is -4. Obviously, the possible combined score values for S1 are -4, -3, -2, -1, 0, 1, 2, 3, and 4.

[0264] An overview of the exemplary S1 synthesis opinion based on the combined score value is as follows.

[0265] If the combined score = -4 or -3, then the S1 synthesis opinion = strong left anteroposterior excess.

[0266] If the combined score = -2, then the S1 synthesis opinion = left anteroposterior excess trend.

[0267] If the combined score = 2, then the S1 synthesis opinion = right anteroposterior excess trend.

[0268] If the combined score = 4 or 3, then the S1 synthesis opinion = strong right anteroposterior excess.

[0269] If the combined score = 0, then no opinion.

[0270] A similar synthesis opinion derivation applies to the vertical and horizontal directions.

[0271] Return reference Figure 35 , the exemplary text report shows that S1 = excessive development in the right anterior-posterior direction, S2 = none, and S3 = a tendency of left upper deviation.

[0272] In very rare cases, the synthesis opinion is shown in all three directions, or the opinion presents a certain type of synthesis opinion mixture, which may suggest further extended diagnosis and / or treatment.

[0273] In addition, the selected exemplary method and / or device embodiments according to the present application can also provide a rapid visual assessment of the asymmetry characteristics of the maxillofacial / dental structure of the patient.

[0274] Figure 36 is a drawing or chart showing the maxillofacial / dental structure characteristics of the patient relative to the front view, and the drawing or chart is drawn using markers, reference markers 414 (see Figure 5 ) selected by the operator. This type of displayed drawing clearly shows the asymmetry (left vs. right) of this exemplary patient in an objective manner.

[0275] Similarly, Figure 37 is a drawing or chart of the sagittal view, where the reference markers 414 show how closely the left and right sides of the patient's face overlap, which serves as another objective indicator of asymmetry.

[0276] Figure 38 is a drawing or chart that provides a rapid visual assessment of the obvious improper alignment of the patient's occlusion in the sagittal view of the upper jaw plane 704 and the lower jaw plane 702. The upper jaw plane 704 is calculated based on the derived upper jaw markers 814, and the lower jaw plane 702 is calculated based on the derived lower jaw markers 814. The derived markers 814 are based on Figure 4 the segmented teeth 304 shown and show the positions of the teeth. Figure 38 The example shown depicts exemplary visual cues for a patient with a high-angle facial type.

[0277] Embodiments of the present disclosure use measurements of the relative positions of teeth and related anatomical structures from CBCT, optical scanning, or both as inputs to an analysis processor or engine for maxillofacial / dental biometrics. The biometric analysis processor uses artificial intelligence (AI) algorithms and related machine learning methods to generate diagnostic orthodontic information that can be used for patient evaluation and ongoing treatment. Using the generated AI output data and analysis from the biometric analysis processor, the AI inverse operation then generates and displays quantitative data to support corrective orthodontics.

[0278] According to an embodiment of the present disclosure, the described method provides an automated solution for defining an optimal arch form based on the tooth positions of an individual patient prior to orthodontic treatment.

[0279] It can also provide guidance for using dental appliances (including designs, uses, placement arrangements, and combinations of one or more aligners, braces, positioners, retainers, etc.). To support the deployment of orthodontic appliances, embodiments of the present disclosure provide guidance for a multi-step process towards achieving an optimal arch form. For an individual patient, the method calculates a set of multiple recommended motion vectors that can be used to guide tooth repositioning. According to an alternative embodiment, if feasible, one or more of the appropriate dental appliances can be manufactured in whole or in part using a 3D printer; alternatively, an appropriate appliance can be assembled using an arrangement of standard brackets and braces.

[0280] Figure 39 The flowchart of shows a logical flowchart of the logical processing mechanism and data that can be used to provide evaluation and guidance to support orthodontic applications. Biometric data 3900 obtained from CBCT, optical scans, or other sources, as well as population data, are input into the biometric analysis processor 3910. In response, the biometric analysis processor 3910 (i.e., an artificial intelligence (AI) engine) performs calculations as previously described and generates descriptive statements 3920 that identify one or more dental / maxillofacial deformities. According to an exemplary embodiment of the present disclosure, the descriptive statements that describe one or more dental / maxillofacial deformities may include some of those previously given in Figures 31A to 32D those given previously.

[0281] Continue Figure 39 In the process of, the AI inverse processor 3930 provides a logical engine that generates recommended or desired arch curve data 3904, which is based on and generated from the anatomy of the individual patient. Based on the descriptive statements 3920 and based on the desired arch curve data 3904, the AI inverse processor 3930 then generates corresponding correction data 3940, which may include the motion vectors required for tooth repositioning and related data for orthodontic guidance.

[0282] AI inverse processing can start with arch form optimization. Figure 40 The exemplary situation shown shows an image of a typical patient condition (i.e., a left turn of the arch with an angle α). A non-zero angle indicates asymmetry in the tooth arch form. The sequence performed for arch rotation correction provides an example of the activities of the AI inverse processor 3930 for this typical situation. The following summarizes the sequence steps:

[0283] 1. The AI engine (i.e., Figure 39The biometric analysis processor 3910 analyzes biometric data from CBCT reconstruction and generates a descriptive statement indicating Figure 40 the described left rotation condition of the dental arch.

[0284] 2. The AI inverse engine (i.e., the AI inverse processor 3930) generates patient-specific, inherent, and optimized geometric primitives and related parameters indicating the quantified tooth movement values for the current stage of the treatment process based on the descriptive statement and based on the recommended or desired results of the dental arch characteristics.

[0285] For Figure 40 example:

[0286] (i) The AI engine detects an arch rotation of the function f(t) of the tooth vector t representing the set {t1, … t N}, where N is the number of teeth in the dental arch. The position of t (in an exemplary 2D space) can be corrected by the inverse operation of the AI engine by rearranging the teeth t so as to minimize the arch rotation in a systematic and automated manner: min f(t);

[0287] This expression is subject to an exemplary function:

[0288] g(t) = a 4th-order polyline curve, and the exemplary function in turn leads to solving an overdetermined system in the exemplary 2D space: X T β = y;

[0289] where X T represents a matrix containing the 0th to nth order x positions of all the teeth in the exemplary 2D space. An exemplary value is n = 4.

[0290] The variable y represents a vector {y1,..y N} containing the 1st-order y positions of all the teeth in the exemplary 2D space; again, the variable N is the number of teeth included in the dental arch.

[0291] where β represents a vector {β0Λβ n} with the following objective function.

[0292]

[0293] The concept of the correction method applies to 3D space.

[0294] (ii) To achieve the objective of min(f(t) = α), the sequence can be as follows:

[0295] (1) First, calculate the tensor matrix:

[0296] I = I d trace(C) - C; where

[0297] For 2D or 3D calculations, d = 2 or 3 respectively;

[0298] p k represents the (x, y, z) position vector of an element (e.g., a voxel of a tooth).

[0299] In Figure 40 the case of dental arch rotation, p k is the center of inertia of tooth k. k = {1, 2, 3,... N}. Again, the variable N is the number of teeth included in the dental arch. Figure 41 An exemplary representation of the center of inertia p along the dental arch is shown in a 3D perspective view k 4100. Embodiments of the present disclosure display the center of inertia in a 2D plane, thereby showing a recommended adjustment for positioning the center of inertia. The procedure for generating the recommended adjustment can alternatively be extended to orthodontics in 3D space.

[0300] (2) Second, calculate the eigenvectors of the tensor I to calculate the dental arch rotation angle α;

[0301] (3) Third, use the tooth center of inertia as p k input points to calculate the dental arch curve, such as g(t) = 4th order polyline curve.

[0302] It should be noted that additional input points can be utilized to increase the set of the center of inertia p k , or alternatively the set can be reduced in size by removing outlier input points. Exemplary additional input points can be the original center of inertia with a flipped sign (x - direction); exemplary outlier points can be those whose coordinates show a significant deviation from the ideal dental arch shape.

[0303] To simplify the problem, a 4th order polyline - curve (polynomial curve) can be calculated in the (x, y) space (i.e., in the case where the variable d = 2) Figure 42 shows the center of inertia 4100 plotted along an initial uncorrected piece - wise linear dental arch curve 4202 in the x, y space (2D) with 14 teeth. A few of the centers of inertia 4100 are denoted by exemplary coordinates {(x1, y1), (x2, y2),...(x 14 , y 14 )} marked.

[0304] The polyline - curve (polynomial curve) can be obtained by minimizing: to obtain the polyline - curve (polynomial curve) calculation;

[0305] where y i is an element of {y1,..y N}, xij is the matrix X T element. The above S(β) equation represents an overdetermined linear system that can be solved, for example, by using well-known pseudoinverse methods familiar to those skilled in the art. After this calculation, then, it can be directly mapped Figure 42 to the tooth center of inertia 4100 shown. In a direct mapping method, each center of inertia p k of 4100 in the x n value is fixed, and the y n value is adjusted to vertically shift the center of inertia to the polynomial curve above. As Figure 43 shown, the individual tooth centers of inertia p k 4100 can be vertically moved a small amount to fit the polynomial curve while keeping the corresponding x value constant.

[0306] The original uncorrected center can also be moved to the polynomial curve by appropriately selecting one of the roots of the nth-order polynomial curve, thereby keeping the y n value as a fixed input and making the x n (root) the output. Then, the moved center can be used to recalculate the tensor matrix I. The eigenvectors of the tensor can be recalculated and the dental arch rotation angle α( ) can be recalculated. Figure 40 )

[0307] The above process can be repeated until the angle α reaches a predetermined minimum value or zero (indicating a symmetric tooth arch form).

[0308] Figure 43 shows the desired optimized arch curve 4300 overlaid for comparison with the original arch form before optimization calculated as previously described.

[0309] The recommended movement of the teeth from their original position to the desired position based on the computational optimization can be shown and reported to the practitioner, as Figure 44 shown.

[0310] In Figure 44 the reported data, the original tooth centers of inertia 4100 of the dental arch can be shown (such as highlighted in a specific color or using other suitable display processing). The movement vector V then shows the desired movement from the position of the original center of inertia 4100 to the optimized center of inertia 4110. The original dental arch rotation is represented by the vector 4106. The corrected dental arch rotation angle α is represented by the vector 4108.

[0311] Figure 45 shows a graph indicating the tooth displacement vector V based on the above calculations. Figure 46A diagram is shown in which the vector displacement is decomposed into mutually orthogonal tangential component directions and normal component directions.

[0312] For Figure 40 the example shown, the corrected data of the tooth displacement vector can help serve as a guide for orthodontic treatment. Exemplary optimized fourth-order polynomial curve intercept and coefficient parameters can be as follows:

[0313] 23.174417248277855;

[0315] -0.000000000000000;

[0316] -0.037164341067977; 0.000000000000000;

[0318] -0.000018751015683.

[0319] According to an embodiment of the present disclosure, the system will Figure 46 data of the type presented in to a practicing doctor in a certain form to support an orthodontic treatment plan for a patient. For each tooth in the dental arch, a corresponding vector V is calculated based on a recommended or desired adjustment of the position of the center of inertia of the tooth.

[0320] Multi-stage implementation

[0321] An alternative embodiment of the present disclosure extends the logic for tooth position adjustment to more closely correspond to a multi-stage sequence for orthodontic treatment. This embodiment provides multiple iterations of the repositioning calculation and reporting process to more closely track patient progress to recommend necessary adjustments at each stage.

[0322] The system of the present disclosure receives first position data of components (teeth) of a patient's dentition at time T0, where the digital data is extracted by an AI engine from at least one 3D digital volume acquisition modality applied to the dentition. The 3D volume can be acquired by using a CBCT scanner or an optical scanner or a laser scanner.

[0323] The system of the present disclosure automatically generates second position digital data of components (teeth) of the patient's dentition based on the first position digital data of the dentition components by an inverse operation of the AI engine, where the second position digital data is highly optimized such that at time T1 after orthodontic treatment, the resulting dental arch form of the dentition components (teeth) is an improved fit for multiple aesthetic and functional requirements.

[0324] Figure 47 And Figure 48Shows the succession of arch improvements achieved by phased tooth movement using the iterative arch approximation calculations described herein. Figure 47 The graphical representation shows a first step performed using an AI inverse operation on an arch shape from a 3D volume obtained by using a CBCT scanner or an optical scanner or a laser scanner. The dashed line in the locally enlarged section shows the part of the arch curve after the original patient data is extracted at time T0.

[0325] In practice, at time T0, both a CBCT scan and an intraoral optical scan have been obtained. A 3D tooth model with roots can be generated based on the CBCT scan; a 3D crown model without roots can be generated based on the intraoral optical scan. Then, the crown model without roots and the tooth model with roots can be recorded at time T0.

[0326] At Figure 47 and Figure 48 In the process shown, the previously described tooth arch morphology optimization protocol is applied to the data obtained at time T0, thereby generating a first set of motion vectors V1. These initial movement vectors can be considered a "scaled" or "reduced" version of the full-size movement vector V Figure 46 described, for example, V1 = 0.5V.

[0327] These scaled vectors provide data for a single stage in the treatment protocol. Regarding, for example, Figure 47 the arch mapping chart, the vector V1 provides the indicated movement of the corresponding tooth center of inertia from time T0 to time T1.

[0328] Using this multi-stage sequence, the iterative logic repeats its processing at the end of the first stage, effectively using the second position data at time T1 as the starting point, such that the T1 position replaces the T0 position and the processing continues.

[0329] In practice, at time T k where k>0, a 3D crown model without roots can be obtained by using an intraoral optical scanner without obtaining another CBCT scan; this sequence helps reduce patient X-ray exposure. The tooth model with roots obtained at time T0 can be aligned with the crown model without roots at time T k such that a new set of tooth models with roots aligned with the crown model without roots is formed at time T k This new set of tooth models with roots can be used to evaluate the treatment efficacy. A revised treatment plan can be designed and a new set of tooth movement vectors can be calculated accordingly.

[0330] Through subsequent AI inverse operations, the system of the present disclosure generates another second position digital data of the patient's dentition based on the new first position digital data calculated at time T1. As Figure 48 shown, the optimization of the calculated patient dentition generates a further improved arch form by generating a new position at time T2 using movement along vector V2. After orthodontic treatment, the resulting arch form provides an improved fit of the dentition components (teeth) to aesthetic and functional requirements.

[0331] Reference Figure 47 and Figure 48 The exemplary two-stage process (T0-T1, T1-T2) described can be generalized as a multi-stage process represented by T i -T i+1 In general, the multi-stage process can be terminated at time Tn when the difference between the first position digital data and the second position data decreases. Alternatively, the completion of the multi-stage adjustment process can be determined using, for example, a pre-defined number of iterations or by estimating other movement distances according to a predetermined threshold.

[0332] As Figure 46 、 Figure 47 and Figure 48 shown in the examples of, the system of the present disclosure can automatically decompose the displacement data of the second position data along the tangential and normal directions relative to the resulting arch form at time T i (where i = 0, 1, 2, 3,... n-1). i At time T

[0333] The process of the present disclosure can automatically determine and / or fabricate a position correction device for the dentition components based on the decomposed displacement data and vector V at time T i If the decomposed displacement data is mainly tangential, braces may be preferred. If the main component of the decomposed displacement data is normal, aligners may be preferred. In many cases, a combination of aligner and brace devices is preferred. The vector V for each step in the process can be reported (such as displayed, printed, or stored) and provided to an appliance design system, which provides the fabrication of a suitable brace, aligner, or other dental appliance for tooth repositioning, as described in more detail subsequently.

[0334] For example, Figure 49 shows a computer-generated list of the movement vectors V for each of the 14 teeth of the dental arch of an orthodontic patient. The values of the x-axis movement and y-axis movement of each tooth vector V are shown. The movement vector V values can be provided as a list in a file or the like or displayed to the practitioner.

[0335] Figure 50A(3D Rendered View) shows the arrangement of teeth in the initial uncorrected dental arch 5000 of an exemplary orthodontic patient. Figure 50B Shows the corrected dental arch 5010 after treatment recommendations provided by the system of the present disclosure. Figure 50C (Partially also a 3D rendered view) shows the overlaid initial and optimized dental arches, where the original tooth positions are indicated by the contour lines 5002. Figure 50D (Slice of a 2D axial view) shows another example where the initial dental arch in contour lines 5002 is overlaid on the optimized dental arch 5010.

[0336] For example, Figure 51 The schematic diagram of shows the operator interface display 5100 for controlling the process to provide orthodontic data and for displaying the processing results. The image portion 5110 provides the actual scan results (as in Figure 50A ), the improved positioning (as in Figure 50B ), and the graphical representation of the vector V of the proposed tooth movement (as in Figure 46 ). These different displayed data can be, for example, overlaid or shown separately when selected by the operator using the controls 5120. The operator can also select different calculations and results according to variable selections such as for single-stage or multi-stage treatment, as referenced in [[ID=27 and ​ as described.

[0337] Embodiments of the present disclosure can generate vector and positioning information suitable for various types of appliance manufacturing systems. ​ The schematic diagram of shows an exemplary manufacturing system 260 for forming an orthodontic appliance using the optimization method of the present disclosure. Image data from an imaging device 270 (such as the CBCT imaging device 100 as described in reference to ​ ) can be provided as a data file or streaming data via a wired or wireless network 282 (such as Ethernet with Internet connectivity). The network 282 can be used to transfer this 3D image data to the memory 284 or a storage on a networked server or workspace 280. The patient's clinical indications and relevant parameters can be entered or otherwise associated with the 3D data via the workspace 280. An automated or partially automated process can then be executed at the workspace 280 to generate an appliance design by forming a print file 288 or other data structure to support appliance manufacturing. The print file 288 or other manufacturing instructions can go to the manufacturing device 290, which also communicates signals with the network 282.

[0338] ​The manufacturing process can be highly automated or partially automated, or it can be a manual manufacturing process that uses the vector 10 data provided by the system. According to an embodiment of the present disclosure, the manufacturing device 290 is a networked 3D printer that can be used to generate various arrangements of aligners or other orthodontic appliances. An operator or practitioner at the workspace 280 can provide various control functions and commands for operating the 3D printer using the biometric analysis tools described herein. Other types of manufacturing devices 290 may require additional setup or control and may require more extensive operator interaction or practitioner input in order to apply the biometric analysis results.

[0339] ​ The flowchart shows a sequence for applying the results of orthodontic optimization to orthodontic appliance design and manufacturing tasks. The biometric acquisition step S5310 obtains the biometric data described above to characterize the cephalometric geometry of interest for orthodontic treatment. Then, the biometric processing step S5320 performs processing on the cephalometric data, thereby generating ​ data of the type that describes one or more types of dental / maxillofacial deformities as shown in the example of. Then, the vector generation step S5330 generates correction data that indicates the desired movement vectors of the individual teeth as referred to in ​ reference. The correction data can be generated using, for example, the AI inverse processor described previously. This correction information can be integrated with the treatment plan in the treatment plan generation step S5340. The operator input entry step S5350 can provide additional data for supporting the design processing step S5360, which can be fully automated, partially automated, or mainly manual. The output of the design processing step S5360 (such as the print file 288 or the design data stream) goes to the manufacturing step S5370, which is executed by a manufacturing system (such as a 3D printer or other device for manufacturing orthodontic appliances).

[0340] According to an embodiment of the present disclosure, the design processing step S5360 converts the movement vector data automatically generated for the treatment plan into design data that supports the automated manufacturing of a suitable dental orthodontic appliance. As its output, the design processing step S5360 can generate a file or data stream suitable for 3D printing, such as a file in.STL (Standard Tessellation Language) format commonly used with 3D printers, or a file in.OBJ format that represents 3D geometry. Other types of print file data can be in a proprietary format, such as the X3G or FBX format.

[0341] An automated manufacturing system can be additive, such as a 3D printing device using stereolithography (SLA) or other additive methods that generate an object or form by depositing small amounts of material onto a substrate. Some alternative methods for additive manufacturing include: fused deposition modeling, which applies a material in a liquid state and allows the material to harden; and selective laser sintering, which uses focused radiant energy to sinter metal, ceramic, or polymer particles for forming a structure. Alternatively, the automated manufacturing device can be subtractive, such as a computer numerical control (CNC) device used to machine an orthodontic appliance from a suitable piece of material.

[0342] User interaction can be used as part of the manufacturing process, such as verifying and validating automatically generated and displayed results, or modifying the generated results at the discretion of a practicing physician. Thus, for example, an operator may receive a certain guidance from an automated system but may still change the generated movement vector data according to the specific patient needs. Alternatively, an operator at a design workspace may input and manipulate design data to generate a customized orthodontic appliance design for a patient.

[0343] Described herein is a computer-executed method that extends and enhances 3D cephalometric analysis of a patient's maxillofacial asymmetry to provide orthodontic evaluation and guidance for subsequent treatment, including manufacturing a suitable dental appliance using manual or automated methods.

[0344] Consistent with the exemplary embodiments herein, a computer program can use stored instructions that perform 3D biometric analysis on image data accessed from an electronic memory. As those skilled in the art of image processing can appreciate, the computer programs for operating an imaging system and a probe and acquiring image data in the exemplary embodiments of the present application can be utilized by a suitable general-purpose computer system operated as a control logic processor (such as a personal computer or a workspace) as described herein. However, many other types of computer systems can be used to execute the computer programs of the present invention, including, for example, an arrangement of networked processors. The computer programs for executing the exemplary method embodiments can be stored in a computer-readable storage medium. Such a medium can include, for example; magnetic storage media, such as disks (such as a hard disk drive) or removable devices or magnetic tapes; optical storage media, such as optical discs, optical tapes, or machine-readable optical encodings; solid-state electronic storage devices, such as random access memory (RAM) or read-only memory (ROM); or any other physical device or medium for storing a computer program. The computer programs for executing the exemplary method embodiments can also be stored on a computer-readable storage medium connected to an image processor via the Internet or other networks or communication media. Those skilled in the art will further readily recognize that equivalents of such computer program products can also be constructed in hardware.

[0345] It should be noted that the term "memory", which is equivalent to "computer-accessible memory" in the context of the present application, may refer to any type of temporary or more persistent data storage work area for storing and manipulating image data and accessible by a computer system, including, for example, a database. The memory may be non-volatile, using, for example, long-term storage media such as magnetic storage devices or optical storage devices. Alternatively, the memory may have a more volatile nature, using electronic circuits such as random access memory (RAM) used by a microprocessor or other control logic processor device as a temporary buffer or work area. For example, display data is typically stored in a temporary storage buffer that is directly associated with the display device and is refreshed periodically as needed to provide the displayed data. When this term is used in the present application, this temporary storage buffer is also considered a type of memory. The memory also serves as a data work area for performing and storing intermediate and final results of calculations and other processing. The computer-accessible memory can be volatile, non-volatile, or a hybrid combination of volatile and non-volatile types.

[0346] It will be understood that the computer program product of the present application may utilize various image manipulation algorithms and well-known processes. Such algorithms and systems, as well as additional aspects of hardware and / or software for generating and otherwise processing images or operating in cooperation with the computer program product of the exemplary embodiments of the present application, are not specifically shown or described herein and may be selected from such algorithms, systems, hardware, components, and elements known in the art.

[0347] While the invention has been shown with respect to one or more implementations, changes and / or modifications may be made to the illustrated examples without departing from the spirit and scope of the appended claims. Additionally, while a particular feature of the invention may have been disclosed with respect to only one of several implementations / embodiments, such feature may be combined with one or more other features of the other implementations / embodiments as may be desired and advantageous for any given or particular function. The term "at least one of..." is used to mean that one or more of the listed items may be selected. The term "about" indicates that the listed value may be slightly changed, provided that the change does not cause the process or structure to be inconsistent with the illustrated embodiments. Finally, "exemplary" indicates that the description is used as an example and does not imply that it is ideal. Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and examples be considered exemplary only, and that the true scope and spirit of the invention be indicated at least by the appended claims.

Claims

1. A method for orthodontic treatment planning, the method being at least partially performed by a computer device, the method comprising: (a) obtaining three-dimensional data from scans of a patient's maxillofacial and dental anatomy; (b) calculating a plurality of cephalometric values based on the obtained three-dimensional data; (c) processing the calculated cephalometric values and generating an indicator indicative of an initial tooth positioning along the patient's dental arch; (d) analyzing the generated indicator to calculate a desired movement vector (V) for each tooth within the dental arch; (e) after applying the desired movement vector (V) to each tooth within the dental arch, generating an indicator indicative of a corrected tooth positioning along the patient's dental arch; and (f) displaying both the generated indicator for the initial tooth positioning and the generated indicator for the corrected tooth positioning along the dental arch in an overlaid manner, as well as the calculated desired movement vector (V).

2. The method according to claim 1, further comprising: Storing and / or transmitting both the generated indicator for the initial tooth positioning and the generated indicator for the corrected tooth positioning, as well as the calculated desired movement vector (V).

3. The method according to claim 1, further comprising: Decomposing the calculated desired movement vector (V) along orthogonal tangent and normal directions and displaying vector data indicative of the decomposition.

4. The method according to claim 1, wherein, Obtaining the three-dimensional data includes: obtaining data from a cone beam computed tomography system and / or an intraoral optical scanner.

5. The method according to claim 1, further comprising: Manufacturing one or more orthodontic appliances based on the calculated desired movement vector (V).

6. The method according to claim 5, wherein, Transmitting the calculated desired movement vector (V) includes: transmitting to an automated manufacturing device.

7. The method according to claim 5, wherein, Manufacturing includes: Receiving an operator command related to desired tooth movement.

8. The method according to claim 1, wherein Processing to generate a target dental arch form using patient anatomy and population data; and / or wherein, processing specifies a predetermined target dental arch form based on patient anatomy and population data.

9. The method according to claim 1, wherein, The desired movement vector shows a repositioning of the center of inertia of the teeth for orthodontic treatment with a single stage; and / or wherein, The desired movement vector shows a repositioning of the center of inertia of the teeth for a single stage of orthodontic treatment with multiple stages.

10. The method according to claim 1, wherein, The calculated movement vector is provided as a list of coordinate values.

11. The method according to claim 1, wherein, Displaying the movement vector further includes: displaying the vector overlaid on a 2D contour line of the teeth within the dental arch for actual or desired tooth movement; and / or wherein, displaying the movement vector further includes: displaying the vector overlaid on a 3D representation of the teeth in certain portions of the dental arch.

12. The method according to claim 1, further comprising: Generating a 3D printing file based on the calculated movement vector.

13. A method for manufacturing a position correction device using the generated indicator for the initial tooth positioning and the generated indicator for the corrected tooth positioning, as well as the calculated desired movement vector (V) in the method according to any one of the preceding claims.

14. A device for providing guidance for orthodontics, the device comprising: (a) a scanning device configured to obtain three-dimensional data from scans of a patient's maxillofacial and dental anatomy; (b) a computer device programmed with instructions for: (i) Calculate a plurality of cephalometric values based on the obtained three-dimensional data; (ii) Process the calculated cephalometric values and generate an index indicating an initial tooth positioning along the patient's dental arch; (iii) Analyze the generated index to calculate an expected movement vector for each tooth within the dental arch; (iv) After applying the expected movement vector to each tooth within the dental arch, generate an index indicating a corrected tooth positioning along the patient's dental arch; And a display communicates with the computer device for displaying both the generated index for the initial tooth positioning and the generated index for the corrected tooth positioning along the dental arch in an overlaid manner and the calculated expected movement vector (V).

15. The apparatus according to claim 14, further comprising a manufacturing device for automatically manufacturing a dental appliance using both the generated index for the initial tooth positioning and the generated index for the corrected tooth positioning and the calculated expected movement vector (V), wherein the manufacturing device communicates with the computer device in a signal manner.

Images