# US 11,443,494 B2 · Method for estimating at least one of shape, position and orientation of a dental restoration > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,443,494 B2 - Document ID: US11443494B2 - Status: Granted - Kind: B2 - Application number: 16/223,604 - Filed: 2018-12-18 - Published: 2019-05-16 - Granted: 2022-09-13 - Earliest claimed: 2016-06-21 - Assignees: Nobel Biocare Services AG - Applicants: Nobel Biocare Services AG - Inventors: Johannes Keustermans; Pieter Van Leemput; Veerle Wouters; Wouter Mollemans - Web page: https://patentgrep.com/patent/US11443494B2 ## CPC - G06T 19/20: Editing of three-dimensional [3D] images, e.g. changing shapes or colours, aligning objects or positioning parts - A61C 7/002: {Orthodontic computer assisted systems} - A61C 8/0001: {Impression means for implants, e.g. impression coping} - A61C 8/0096: {Implants for use in orthodontic treatment} - A61C 9/004: {Means or methods for taking digitized impressions} - A61C 13/0004: {Computer-assisted sizing or machining of dental prostheses} - G06F 30/17: Mechanical parametric or variational design - G06F 30/20: Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) - G06T 17/20: Finite element generation, e.g. wire-frame surface description, {tesselation} - G06T 2210/41: Medical - G06T 2219/2004: Aligning objects, relative positioning of parts - G06T 2219/2016: Rotation, translation, scaling - G06T 2219/2021: Shape modification - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - A61C: DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE (non-driven toothbrushes A46B; {tongue scrapers A61B17/24;} preparations for dentistry A61K6/00; preparations for cleaning the teeth or mouth A61K8/00, A61Q11/00) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A method is provided for obtaining an estimation of the shape, position and/or orientation of one or more existing teeth of a patient or of one or more teeth to be included in a dental restoration destined to replace one or more missing teeth in a partially edentulous patient. The method involves adapting a virtual teeth setup to the intra-oral anatomical situation of the patient, wherein said virtual teeth setup includes separated surface meshes of individual teeth positioned in a dental arch or segment thereof. The virtual teeth setup is adapted by optimizing an energy function, which represents a quality measure for said virtual teeth setup, and using a statistical model, which describes for a given dentition or segment thereof a probability distribution for at least the shapes of individual teeth, the relations between shapes of neighbouring teeth and/or relations between positions and/or orientations of neighbouring teeth. The adapted virtual teeth setup resulting from said optimized energy function is subsequently used to estimate said sought for shape, position and/or orientation. ## Claims ### Claim 1 A computer assisted method for estimating a shape, position and orientation of a dental restoration for a partially edentulous patient, the method comprising: indicating one or more teeth requiring a dental restoration, for which an estimation of said shape, position and orientation is to be generated, and indicating a remaining tooth or teeth available for estimating; providing a virtual teeth setup comprising one or more teeth corresponding to the one or more teeth requiring said dental restoration as well as one or more teeth corresponding to the indicated remaining tooth or teeth, wherein said virtual teeth setup comprises separated surface meshes of individual teeth positioned in a dental arch or segment thereof; providing a digitized surface mesh of an intra-oral region of said patient comprising said indicated remaining tooth or teeth and the region of the one or more teeth requiring said dental restoration; applying and optimizing an energy function, representing a quality measure for said virtual teeth setup, by adapting the virtual teeth setup to one or more of said indicated remaining tooth or teeth in said digitized surface mesh of the intra-oral region of said patient given a statistical model, for a given dentition or segment thereof, for (i) the shapes of individual teeth, (ii) relations between shapes of neighbouring teeth and (iii) relations between positions and/or orientations of neighbouring teeth, said energy function comprising a first measure indicative of a fit between said patient's anatomy and said adapted virtual teeth setup, and a second measure indicating a probability of said adapted virtual teeth setup given said statistical model; and estimating said shape, position and orientation of said dental restoration using the adapted virtual teeth setup resulting from said applied and optimized energy function. ### Claim 2 (depends on 1) The method of claim 1, further comprising postprocessing to take into account the shape of an antagonist crown of a tooth in said adapted virtual teeth setup by defining occlusal contact points and deforming the shape of said tooth of said adapted virtual teeth setup to obtain a desirable occlusal contact at said defined contact points. ### Claim 3 (depends on 1) The method of claim 1, further comprising fitting of a crown from a library to a tooth of said adapted virtual teeth setup. ### Claim 4 (depends on 1) The method of claim 1, further comprising exporting said estimated shape, position and orientation of said dental restoration. ### Claim 5 (depends on 1) The method of claim 1, further comprising: receiving user input modifying at least one of a shape, position and orientation of a tooth requiring dental restoration as estimated for said tooth using said adapted teeth setup resulting from said optimized energy function, applying and optimizing a second energy function, representing a quality measure for said adapted virtual teeth setup, to adjust said adapted virtual teeth setup to said indicated remaining tooth or teeth in said digitized surface mesh of the intra-oral region of the patient considering the constraint provided by said inputted modification for said tooth requiring restoration and given said statistical model, said second energy function comprising a first measure indicative of a fit between said patient's anatomy and said adjusted and adapted virtual teeth setup given said constraint, and a second measure indicating a probability of said adjusted and adapted virtual teeth setup given said statistical model, and re-estimating said at least one element of said shape, position and orientation of said dental restoration using the adjusted and adapted virtual teeth setup resulting from said applied and optimized second energy function. ### Claim 6 (depends on 5) The method according to claim 5 wherein said inputted modification of at least one of a shape, position and orientation for a tooth requiring restoration is a hard constraint in said adjusting. ### Claim 7 (depends on 5) The method according to claim 5 wherein said inputted modification of at least one of a shape, position and orientation for a tooth requiring restoration is a soft constraint in said adjusting. ### Claim 8 (depends on 1) The method according to claim 1, further comprising postprocessing to prevent neighbouring teeth in said adapted virtual teeth setup from overlapping with each other by iteratively detecting maximal overlapping points and modifying said tooth shape to remove said overlap. ### Claim 9 (depends on 1) The method according to claim 1, wherein said first measure comprises a landmark term indicative of a distance between corresponding landmarks on said virtual teeth setup and on said digitized surface mesh of the intra-oral region of the patient. ### Claim 10 (depends on 1) The method according to claim 1, wherein said first measure comprises a surface term indicating, for points of said virtual teeth setup, a distance to said digitized surface mesh of the intra-oral region of the patient. ### Claim 11 (depends on 1) The method according to claim 1, wherein said energy function comprises a contact point term providing a measure for a distance between contact point sets of neighbouring teeth. ### Claim 12 (depends on 1) The method according to claim 1, wherein said energy function comprises a symmetric shape, position and/or orientation term giving a symmetry measure for the shape, position and/or orientation of two contralateral teeth. ### Claim 13 (depends on 1) The method according to claim 1, wherein said energy function takes into account one or more heuristic rules defining a relation between the positions of predefined landmarks on teeth of said adapted virtual teeth setup. ### Claim 14 (depends on 1) The method according to claim 1, wherein said energy function takes into account one or more heuristic rules defining a relation between distances in-between predefined landmarks on teeth of said adapted virtual teeth setup. ### Claim 15 (depends on 1) The method according to claim 1, wherein said statistical model is obtained using a training phase, which comprises: providing a multitude of virtual teeth setups comprising digital surface meshes of different near-ideal teeth setups and wherein the individual teeth are available as separated surface meshes, computing a mean virtual teeth setup from said multitude of virtual teeth setups, and computing from said multitude of virtual teeth setups the statistical model for at least (i) the shapes of individual teeth, (ii) the relations between shapes of neighbouring teeth and (iii) the relations between positions and/or orientations of neighbouring teeth. ### Claim 16 (depends on 15) The method according to claim 15, wherein said virtual teeth setups are obtained by extracting the individual teeth surfaces from a surface mesh of scans of dental casts or impressions or of intra-oral scans obtained from individuals having a near-ideal teeth setup. ### Claim 17 (depends on 1) The method according to claim 1, wherein said second measure of said energy function is composed of three separate terms corresponding to said shape of said individual teeth, said relations between said shapes of said neighbouring teeth and said relations between said positions and/or orientations of said neighbouring teeth, respectively. ### Claim 18 A computer based method for estimating a shape, position and orientation of one or more teeth from a digitized intra-oral surface of a patient, said method comprising: indicating the one or more teeth which require said estimation; providing a virtual teeth setup comprising one or more teeth corresponding to said one or more teeth requiring said estimation, wherein said virtual teeth setup comprises separated surface meshes of individual teeth positioned in a teeth arch or segment thereof; providing a digitized surface mesh of an intra-oral region of said patient comprising said one or more indicated teeth requiring said estimation; applying and optimizing an energy function, representing a quality measure for said virtual teeth setup, by adapting the virtual teeth setup to said one or more indicated teeth in said digitized surface mesh of the intra-oral region of said patient given a statistical model, for a given dentition or segment thereof, for (i) the shapes of individual teeth, (ii) relations between shapes of neighbouring teeth and (iii) and/or relations between positions and/or orientations of neighbouring teeth, said energy function comprising a first measure indicative of a fit between said patient's anatomy and said virtual teeth setup, and a second measure indicating a probability of said adapted virtual teeth setup given said statistical model; and estimating said shape, position and orientation for said at least one tooth using said adapted virtual teeth setup resulting from said applied and optimized energy function. ### Claim 19 (depends on 18) The method according to claim 18 wherein said adapted virtual teeth setup provides a second digitized surface mesh representing the intra-oral region of said patient wherein said one or more teeth are available as separated surface meshes of individual teeth. ### Claim 20 (depends on 18) The method according to claim 18, wherein said method is part of a digital orthodontic planning method. ### Claim 21 (depends on 18) The method according to claim 18 further comprising: receiving user input virtually modifying one of the shape, position and orientation of an indicated tooth as estimated for said tooth using the adapted teeth setup resulting from said optimized energy function, applying and optimizing a second energy function, representing a quality measure for said adapted virtual teeth setup, to adjust said adapted virtual teeth setup to said tooth in said digitized surface mesh of the intra-oral region considering the constraint provided by said inputted modification for said tooth and given said statistical model, said second energy function comprising a first measure indicative of a fit between said patient's anatomy and said adjusted and adapted virtual teeth setup given said constraint, and a second measure indicating a probability of said adjusted and adapted virtual teeth setup given said statistical model, and proposing a virtual modification of at least one element of a shape, position and orientation of one or more teeth in said digitized intra-oral surface of a patient resulting from said applied and optimized second energy function. ### Claim 22 (depends on 21) The method according to claim 21 wherein said inputted virtual modification of at least one of a shape, position and orientation of a tooth in said segmented digitized surface mesh is considered as a hard constraint in said adjusting. ### Claim 23 (depends on 21) The method according to claim 21 wherein said inputted virtual modification of at least one of a shape, position and orientation of a tooth in said segmented digitized surface mesh is considered as a soft constraint in said adjusting. ### Claim 24 (depends on 18) The method according to claim 18, further comprising postprocessing to prevent neighbouring teeth in said adapted virtual teeth setup from overlapping with each other by iteratively detecting maximal overlapping points and modifying said tooth shape to remove said overlap. ### Claim 25 (depends on 18) The method according to claim 18, wherein said first measure comprises a landmark term indicative of a distance between corresponding landmarks on said virtual teeth setup and on said digitized surface mesh of the intra-oral region of the patient. ### Claim 26 (depends on 18) The method according to claim 18, wherein said first measure comprises a surface term indicating, for points of said virtual teeth setup, a distance to said digitized surface mesh of the intra-oral region of the patient. ### Claim 27 (depends on 18) The method according to claim 18, wherein said energy function comprises a contact point term providing a measure for a distance between contact point sets of neighbouring teeth. ### Claim 28 (depends on 18) The method according to claim 18, wherein said energy function comprises a symmetric shape, position and/or orientation term giving a symmetry measure for the shape, position and/or orientation of two contralateral teeth. ### Claim 29 (depends on 18) The method according to claim 18, wherein said energy function takes into account one or more heuristic rules defining a relation between the positions of predefined landmarks on teeth of said adapted virtual teeth setup. ### Claim 30 (depends on 18) The method according to claim 18, wherein said energy function takes into account one or more heuristic rules defining a relation between distances in-between predefined landmarks on teeth of said adapted virtual teeth setup. ### Claim 31 (depends on 18) The method according to claim 18, wherein said statistical model is obtained using a training phase, which comprises: providing a multitude of virtual teeth setups comprising digital surface meshes of different near-ideal teeth setups and wherein the individual teeth are available as separated surface meshes, computing a mean virtual teeth setup from said multitude of virtual teeth setups, and computing from said multitude of virtual teeth setups the statistical model for at least (i) the shapes of individual teeth, (ii) the relations between shapes of neighbouring teeth and (iii) the relations between positions and/or orientations of neighbouring teeth. ### Claim 32 (depends on 31) The method according to claim 31, wherein said virtual teeth setups are obtained by extracting the individual teeth surfaces from a surface mesh of scans of dental casts or impressions or of intra-oral scans obtained from individuals having a near-ideal teeth setup. ### Claim 33 (depends on 18) The method according to claim 18, wherein said second measure of said energy function is composed of three separate terms corresponding to said shape of said individual teeth, said relations between said shapes of said neighbouring teeth and said relations between said positions and/or orientations of said neighbouring teeth, respectively. ### Claim 34 (depends on 18) The method according to claim 18, wherein applying said energy function comprises an optimization over at least one element of a shape, position and orientation of said one or more remaining teeth of said first measure and said second measure. ### Claim 35 (depends on 18) The method according to claim 18, wherein applying said energy function comprises an optimization over said shape, position and orientation of said dental restoration of said second measure.