DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status
Claims 1-30 are currently pending in the application filed August 8, 2022.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55 on November 17, 2021.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 3/28/2024, 12/13/2023, 9/29/2023, 5/08/2023, 3/16/2023, 1/13/2023, 8/29/2022, and 8/8/2022 have been considered by the Examiner.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the drawings for claims 8, 11, 14,16, 19, 24, 27, and 29 must be shown or the feature(s) canceled from the claim(s). No new matter should be entered.
Claim 8 mentions patient and product information however the drawings do not indicate patient and product information clearly.
Claim 11 and 24 mentions dental aligners being specific to detention however the drawings showed no indication of dental aligners being specific to detention.
Claim 14 and 27 mentions translation vectors and rotation components however the drawings showed no indication of translation vectors and rotation components in the drawing.
Claim 16 and 29 mentions dental impression or intraoral scan in the figures however the drawings showed no indication of dental impression or intraoral scan in the figures
Claim 19 mentions loss function however the drawings showed no indication of loss function.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Abstract
The abstract of the disclosure is objected to because use of legal phraseology. Abstract is written similar to claim language. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
The disclosure is objected to because of the following informalities:
[0004] [0005] [0006]: “Detention” should be spelled as “dentitions”
[0037] “Removes gingival form” should be written as “removes gingival from”
[0043] missing beginning parenthesis in “differentiate teeth from gingiva)”
[0005] [0006] missing period in “in the initial position”
Appropriate correction is required.
Claim Objections
Claim 1, 11, 13, 15, 21, 24, 26, 28, and 30 objected to because of the following informalities:
“detention” should be spelled as “dentition”
Appropriate correction is required.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-2, 9-10, 13-20, 21, 26-29 are rejected under 35 U.S.C. 103 as being unpatentable over Anssari (WO 2020048960 A1), LI (US 20210186659 A1) and Pavloskaia (WO0161613A1).
Regarding claim 1, Anssari teaches:
Method (Anssari, [0027]; “a method of training a deep neural network comprises obtaining a plurality of training dental computed tomography scans … wherein training input data obtained from a training dental computed tomography scan represents all teeth and the entire alveolar process and identifies said individual teeth and said jaw bone”)
maintaining, by one or more processors (Anssari, [0025]; “one processor may be configured to create said three dimensional representations … a second further deep neural network may be used to determine labels for the segmented teeth”)
a final position model (Anssari, [0008, line 8];deep neural network) trained to output movement of teeth of a dentition from initial positions (Anssari, [0008, line 8];training input data) to final positions (Anssari, [0008, line 9];to determine a desired final position) given a plurality of compressed three-dimensional (3D) representations of dentitions comprising a plurality of teeth; (Anssari, [0008, line 8];train a deep neural network with training input data obtained from said plurality of training dental computed tomography scans … all teeth and the entire alveolar process and identifies said individual teeth and said jaw bone.)
Anssari fails to teach:
maintaining, by the one or more processors, a geometric encoder model trained to compress a plurality of 3D representations of detentions comprising a plurality of teeth;
generating, by the one or more processors, for each tooth representation, a compressed tooth representation using the geometric encoder model;
Li teaches:
maintaining, by the one or more processors, a geometric encoder model (Li, [0021]; training a machine learning model to form a three-dimensional (3D) dental model) trained to compress (Li, [0005]; reduced parameter representations of 3D teeth) a plurality of 3D representations of detentions comprising a plurality of teeth (Li, [0055]; initial 3D parameters for the 3D model of the individual's dentition.);
generating, by the one or more processors, for each tooth representation, a compressed tooth representation using the geometric encoder model (Li, [0026]; The parametric 3D dental model may include a reduced representation of a 3D dental model. The reduced representation of the 3D dental model may comprise a principal component analysis representation, as mentioned above. The extracted features may include tooth segmentation and/or numbering data);
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari with Li. The motivation for the combination is to be able utilized the geometric encoder model to compress 3D representations (Li, [0056];” In one example, a principal component analysis (PCA) can be implemented to obtain the reduced parameter representation.”)
The combination of Anssari and Li fails to teach:
receiving, by the one or more processors, a first 3D representation of a dentition comprising a plurality of teeth of a patient in an initial position the first 3D representation comprising a plurality of tooth representations
determining, by the one or more processors, tooth movements of the plurality of teeth of the dentition from the initial position to a final position based on applying each compressed tooth representation to the final position model
generating, by the one or more processors, a second 3D representation of the dentition comprising the plurality of teeth of the patient in the final position, wherein generating the second 3D representation comprises:
applying, by the one or more processors, the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position
Pavloskaia teaches:
receiving, by the one or more processors, a first 3D representation of a dentition comprising a plurality of teeth of a patient in an initial position (Pavloskaia;[Page 6, Line 15];” an initial digital data set (IDDS) representing an initial tooth arrangement is obtained (step 202).”), the first 3D representation comprising a plurality of tooth representations (Pavloskaia,[Page 9, Line 8; “Once a 3D model of the tooth surfaces has been constructed, models of the patient's individual teeth can be derived”)
determining, by the one or more processors, tooth movements of the plurality of teeth of the dentition from the initial position to a final position (Pavloskaia,[Page 4, Line 28];“moved from an initial tooth arrangement to a final tooth arrangement.”) based on applying each compressed tooth representation to the final position model (Pavlovskaia,[Page 2, Line 14];“ creating a parametric representation of the digital data set; and displaying the computer model of the teeth using the parametric representation. Implementations of the method include one or more of the following. The parametric representation is a compressed version of the digital data set.”)
generating, by the one or more processors, a second 3D representation of the dentition comprising the plurality of teeth of the patient in the final position (Pavlovskaia, [Page 7 Line 20];” the final teeth arrangement is incorporated into a final digital data set (FDDS) (step 204)”), wherein generating the second 3D representation comprises:
applying, by the one or more processors, the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position (Pavlovskaia, [Page 7 Line 12]; “The IDDS is manipulated using a computer having a suitable graphical user interface (GUI) and software appropriate for viewing and modifying the images. More specific aspects of this process will be described in detail below. Individual tooth and other components may be segmented or isolated in the model to permit their individual repositioning or removal from the digital model. “)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari and Li with Pavloskaia. The motivation for the combination is to be able create a second 3D representation of dentition by applying tooth movements to the first 3D representation (Pavlovskaia, [Page 9 Line 12];” Alternatively, the teeth may be repositioned based on the visual appearance or based on rules and algorithms programmed into the computer. Once an acceptable final arrangement has been created, the final tooth arrangement is incorporated into a final digital data set (FDDS).”)
Regarding claim 2, the combination of Anssari, Li and Pavloskaia teaches:
generating, by the one or more processors, a treatment plan based on the determined tooth movements of the plurality of teeth of the dentition (Pavlovskaia, [Page 4 Line 23]; “Systems and methods are provided for modeling teeth in creating a treatment plan.”) based on the determined tooth movements of the plurality of teeth of the dentition.
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to be able allow create a treatment plan (Pavlovskaia, [Page 21 Line 4];” FIG. 9 is a simplified block diagram of a data processing system 300 that may be used to develop orthodontic treatment plans.”)
Regarding claim 9, the combination of Anssari, Li and Pavloskaia teaches:
receiving, by the one or more processors, validation of the treatment plan based on a clinical assessment. (Anssari, [0004];” A dental data mining system, e.g. comprising a neural network, is used to determine whether determined motions are orthodontically acceptable and whether a determined candidate aligner is the best solution so far.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to be able have a treatment plan validated based on clinical assessment such as finite element analysis. (Anssari, [0004], “In order to determine segmented paths … finite element analysis is applied.”)
Regarding claim 10, the combination of Anssari, Li and Pavloskaia teaches
wherein generating the treatment plan comprises generating, by the one or more processors, a plurality of intermediate 3D representations (Anssari,[0004];” segmented paths (i.e. incremental movements to intermediate positions over time)”) of the dentition showing a progression of the plurality of teeth from the initial position to the final position, wherein each of the plurality of intermediate 3D representations correspond to a respective stage of the treatment plan (Anssari, [004];” At various stages of the process, and in particular after the segmented paths have been defined, the process can, and generally will, interact with a clinician for the treatment of the patient.”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to be able have a treatment with intermediate 3D representation. (Anssari, [0023], “Said at least one processor may be configured to determine said sequence of desired intermediate positions per tooth based on said determined desired final position”)
Regarding claim 13, the combination of Anssari, Li and Pavloskaia teaches:
The method of claim 1, wherein the 3D representations of detentions comprise a plurality of points representing surfaces of each tooth of the dentition (Anssari, [0002];” 3D data set refers to any digital representation of any dentition, e.g. a 3D voxel representation of a filled volume, densities in a volume, a 3D surface mesh, etc.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have points representing a surface. (Anssari; [00150];” In the example of Fig.26, key points are generated for the surface mesh describing the entire volume of all teeth present.)
Regarding claim 14, the combination of Anssari, Li and Pavloskaia teaches:
wherein determining the tooth movements comprises determining, by the one or more processors, three translation components and three rotation components for each compressed tooth representation. (Anssari, [00126];” e.g. 3 vectors of 3 values describing respectively rotations in order, 3 translation values to an origin, and/or 3 values determining applicable scaling”.)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have three translational points and rotation components representing a surface. (Anssari; [00150];” transformation comprising a translation and/or a rotation per tooth (e.g. a transformation matrix or a vector…determine a transformation per tooth for a patient dental computed tomography scan and allows the desired final position per tooth to be determined based on this determined transformation.”)
Regarding claim 15, the combination of Anssari, Li and Pavloskaia teaches:
wherein applying the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position comprises applying a rigid body transformation (Anssari, [0017]; “Applying the indicator indicating the transformation to data obtained from a dental computed tomography scan from before a successful orthodontic treatment would normally result in data obtained from a dental computed tomography scan from after the successful orthodontic treatment”) to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position using the three translation components and the three rotation components.
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have apply the rigid body transformation to the first 3D representation. (Anssari; [00114];” Furthermore, in step 1905, different variations of one 3D data set are generated by applying random rotations to the (downscaled) 3D data and associated canonical coordinates”)
Regarding claim 16, the combination of Anssari, Li and Pavloskaia teaches:
wherein the first 3D representation is obtained based on a dental impression administered by the patient (Li, [0004];” evaluating data (such as three-dimensional scan, or a dental impression) of the individual's teeth or arch.”), or an intraoral scan (Li, [0050];” an intraoral scanner may image an individual's dental arch and generate a virtual three-dimensional model of that dental arch”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have 3D representation obtained on a dental impression by the patient or a intraoral scan. (Li; [0102];” The 2D original photos may be generated from a scan collected directly from the individual (e.g., using an intraoral scanner) or indirectly (e.g., by scanning a mold of the individual's dentition, and/or by receiving digital models of the individuals taken by another, etc.”)
Regarding claim 17, the combination of Anssari, Li and Pavloskaia teaches
wherein the first 3D representation is obtained using a 2D image reconstruction (Li, [0050]; an intraoral scanner may image an individual's dental arch and generate a virtual three-dimensional model of that dental arch)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have 3D representation obtained via 2D image reconstruction. (Li; [0044];” reconstruct a 3D dental model from one or more 2D images of an individual's teeth”)
Regarding claim 18, the combination of Anssari, Li and Pavloskaia teaches
wherein the geometric encoder model is an autoencoder. (Li, [0007];” In one implementation, a 3D geometry optimization framework is provided that includes automated agents configured to use differential rendering techniques on a 3D dental model to form 2D image(s), which are compared against original 2D images of the individual's teeth to update or improve the 3D dental model”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have geometric encoder model which is automated. (Li; [0078];” one or more automated agents … include positions, geometrical properties (contours, etc.), and/or other data that can form the basis of segmenting individual teeth from 2D images of an individual's dental arch.”)
Regarding claim 19, the combination of Anssari, Li and Pavloskaia teaches
wherein the final position model is trained using a loss function based on an actual 3D representation of one or more teeth at a final position (Anssari, [0056]; “In the context of a final position deep neural network, a specific loss function may be utilized during training.”)
and a corresponding transformed 3D representation of one or more teeth at an initial position, (Anssari, [0056]; “a loss function more specific for this problem may make use of dento- physical properties that may be determined based upon the input data and/or may be known to be universally applicable.”)
the transformed 3D representation of one or more teeth at the initial position being transformed by applying a rigid body transformation to a 3D representation of one or more teeth at an initial position. (Anssari, [0074];” Optimization of the internal parameters of the neural network may be achieved utilizing a loss function 930 taking into account the actual to be predicted transformations and attachment types 908 and dento-physical properties 910 and predictions 928.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to utilize the loss function. (Anssari; [0014];” deep neural network by training said deep neural network with a loss function which depends on said determined dento-physical properties”)
Regarding claim 20, the combination of Anssari, Li and Pavloskaia teaches
receiving, by the one or more processors, from a treatment planning terminal, an adjustment to the final position (Anssari, [0082];” the final tooth positions”) of at least one tooth of the plurality of teeth [Anssari, [0082];” Step 1107 comprises creating one or more adjusted 3D models of teeth without collisions”)
and updating, by the one or more processors, the second 3D representation according to the adjustment received from the treatment planning terminal. (Anssari, [0084]; “This report 1123 includes the determined attachment type per tooth 661 and information on the adjustments performed in step 1107.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to be able to adjust and update the final position and second 3D representation respectively. (Anssari; [Fig. 11], step 1107 and step 1123)
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Regarding claim 21, Anssari teaches:
A treatment planning system, comprising: (Anssari, [0006];” automated system for determining an orthodontic treatment plan,”)
one or more processors: (Anssari, [0025]; “one processor may be configured to create said three dimensional representations … a second further deep neural network may be used to determine labels for the segmented teeth”)
memory storing instructions that, when executed by the one or more processors, cause the one or more processors: (Anssari, [0033]; “a random-access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device”)
maintain a final position model (Anssari, [0008, line 8];deep neural network) trained to output movement of teeth of a dentition from initial positions (Anssari, [0008, line 8];training input data) to final positions (Anssari, [0008, line 9];to determine a desired final position) given a plurality of compressed three-dimensional (3D) representations of dentitions comprising a plurality of teeth; (Anssari, [0008, line 8];train a deep neural network with training input data obtained from said plurality of training dental computed tomography scans … all teeth and the entire alveolar process and identifies said individual teeth and said jaw bone.)
Anssari fails to teach:
maintain a geometric encoder model trained to compress a plurality of 3D representations of detentions comprising a plurality of teeth
generate for each tooth representation, a compressed tooth representation using the geometric encoder model
Li teaches:
maintain a geometric encoder model (Li, [0021]; training a machine learning model to form a three-dimensional (3D) dental model) trained to compress (Li, [0005]; reduced parameter representations of 3D teeth) a plurality of 3D representations of detentions comprising a plurality of teeth (Li, [0055]; initial 3D parameters for the 3D model of the individual's dentition.);
generate for each tooth representation, a compressed tooth representation using the geometric encoder model (Li, [0026]; The parametric 3D dental model may include a reduced representation of a 3D dental model. The reduced representation of the 3D dental model may comprise a principal component analysis representation, as mentioned above. The extracted features may include tooth segmentation and/or numbering data);
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari with Li. The motivation for the combination is to be able utilized the geometric encoder model to compress 3D representations (Li, [0056];” In one example, a principal component analysis (PCA) can be implemented to obtain the reduced parameter representation.”)
The combination of Anssari and Li fail to teach:
receive a first 3D representation of a dentition comprising a plurality of teeth of a patient in an initial position the first 3D representation comprising a plurality of tooth representations
determine tooth movements of the plurality of teeth of the dentition from the initial position to a final position based on applying each compressed tooth representation to the final position model
generate a second 3D representation of the dentition comprising the plurality of teeth of the patient in the final position wherein generating the second 3D representation comprises:
apply the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position
Pavloskaia teaches:
receive a first 3D representation of a dentition comprising a plurality of teeth of a patient in an initial position (Pavloskaia; [Page 6, Line 15];” an initial digital data set (IDDS) representing an initial tooth arrangement is obtained (step 202).”), the first 3D representation comprising a plurality of tooth representations (Pavloskaia, [Page 9, Line 8; “Once a 3D model of the tooth surfaces has been constructed, models of the patient's individual teeth can be derived”)
determine tooth movements of the plurality of teeth of the dentition from the initial position to a final position (Pavloskaia, [Page 4, Line 28]; “moved from an initial tooth arrangement to a final tooth arrangement.”) based on applying each compressed tooth representation to the final position model (Pavlovskaia, [Page 2, Line 14]; “creating a parametric representation of the digital data set; and displaying the computer model of the teeth using the parametric representation. Implementations of the method include one or more of the following. The parametric representation is a compressed version of the digital data set.”)
generate a second 3D representation of the dentition comprising the plurality of teeth of the patient in the final position (Pavlovskaia, [Page 7 Line 20];” the final teeth arrangement is incorporated into a final digital data set (FDDS) (step 204)”), wherein generating the second 3D representation comprises:
apply the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position (Pavlovskaia, [Page 7 Line 12]; “The IDDS is manipulated using a computer having a suitable graphical user interface (GUI) and software appropriate for viewing and modifying the images. More specific aspects of this process will be described in detail below. Individual tooth and other components may be segmented or isolated in the model to permit their individual repositioning or removal from the digital model. “)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li with Pavloskaia. The motivation for the combination is to be able create a second 3D representation of dentition by applying tooth movements to the first 3D representation (Pavlovskaia, [Page 9 Line 12];” Alternatively, the teeth may be repositioned based on the visual appearance or based on rules and algorithms programmed into the computer. Once an acceptable final arrangement has been created, the final tooth arrangement is incorporated into a final digital data set (FDDS).”)
Regarding claim 26, the combination of Anssari, Li and Pavloskaia teaches
wherein the 3D representations of detentions comprise a plurality of points representing surfaces of each tooth of the dentition. (Anssari, [0002];” 3D data set refers to any digital representation of any dentition, e.g. a 3D voxel representation of a filled volume, densities in a volume, a 3D surface mesh, etc.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have points representing a surface. (Anssari; [00150];” In the example of Fig.26, key points are generated for the surface mesh describing the entire volume of all teeth present.)
Regarding claim 27, the combination of Anssari, Li and Pavloskaia teaches
wherein determining the tooth movements comprises determining three translation components and three rotation components for each compressed tooth representation. (Anssari, [00126];” e.g. 3 vectors of 3 values describing respectively rotations in order, 3 translation values to an origin, and/or 3 values determining applicable scaling”.)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have three translational points and rotation components representing a surface. (Anssari; [00150];” transformation comprising a translation and/or a rotation per tooth (e.g. a transformation matrix or a vector…determine a transformation per tooth for a patient dental computed tomography scan and allows the desired final position per tooth to be determined based on this determined transformation.”)
Regarding claim 28, the combination of Anssari, Li and Pavloskaia teaches
wherein applying the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position comprises applying a rigid body transformation (Anssari, [0017]; “Applying the indicator indicating the transformation to data obtained from a dental computed tomography scan from before a successful orthodontic treatment would normally result in data obtained from a dental computed tomography scan from after the successful orthodontic treatment”) to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position using the three translation components and the three rotation components.
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have apply the rigid body transformation to the first 3D representation. (Anssari; [00114];” Furthermore, in step 1905, different variations of one 3D data set are generated by applying random rotations to the (downscaled) 3D data and associated canonical coordinates”)
Regarding claim 29, the combination of Anssari, Li and Pavloskaia teaches
wherein the first 3D representation is obtained based on a dental impression administered by the patient (Li, [0004];” evaluating data (such as three-dimensional scan, or a dental impression) of the individual's teeth or arch.”), an intraoral scan of the plurality of teeth of the patient (Li,[0050];” an intraoral scanner may image an individual's dental arch and generate a virtual three-dimensional model of that dental arch”)., or a 2D image of the plurality of teeth of the patient (Li, [0013]; extracting features from the original 2D image;).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia. The motivation for the combination is to have 3D representation obtained on a dental impression by the patient or a intraoral scan. (Li; [0102];” The 2D original photos may be generated from a scan collected directly from the individual (e.g., using an intraoral scanner) or indirectly (e.g., by scanning a mold of the individual's dentition, and/or by receiving digital models of the individuals taken by another, etc.”)
Regarding claim 30, Anssari teaches:
A non-transitory computer readable medium storing instructions: Anssari, [0120];” non-transitory computer-readable storage medium storing a set of instructions capable of being executed by a processor “)
when executed by one or more processors, cause the one or more processors to: (Anssari, [0025]; “one processor may be configured to create said three dimensional representations … a second further deep neural network may be used to determine labels for the segmented teeth”)
maintain a final position model (Anssari, [0008, line 8];deep neural network) trained to output movement of teeth of a dentition from initial positions (Anssari, [0008, line 8];training input data) to final positions (Anssari, [0008, line 9];to determine a desired final position) given a plurality of compressed three-dimensional (3D) representations of dentitions comprising a plurality of teeth; (Anssari, [0008, line 8];train a deep neural network with training input data obtained from said plurality of training dental computed tomography scans … all teeth and the entire alveolar process and identifies said individual teeth and said jaw bone.)
Anssari fails to teach:
maintain a geometric encoder model trained to compress a plurality of 3D representations of detentions comprising a plurality of teeth
generate for each tooth representation, a compressed tooth representation using the geometric encoder model
Li teaches:
maintain a geometric encoder model (Li, [0021]; training a machine learning model to form a three-dimensional (3D) dental model) trained to compress (Li, [0005]; reduced parameter representations of 3D teeth) a plurality of 3D representations of detentions comprising a plurality of teeth (Li, [0055]; initial 3D parameters for the 3D model of the individual's dentition.);
generate for each tooth representation, a compressed tooth representation using the geometric encoder model (Li, [0026]; The parametric 3D dental model may include a reduced representation of a 3D dental model. The reduced representation of the 3D dental model may comprise a principal component analysis representation, as mentioned above. The extracted features may include tooth segmentation and/or numbering data);
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari with Li. The motivation for the combination is to be able utilized the geometric encoder model to compress 3D representations (Li, [0056];” In one example, a principal component analysis (PCA) can be implemented to obtain the reduced parameter representation.”)
The combination of Anssari and Li fail to teach:
receive a first 3D representation of a dentition comprising a plurality of teeth of a patient in an initial position the first 3D representation comprising a plurality of tooth representations
determine tooth movements of the plurality of teeth of the dentition from the initial position to a final position based on applying each compressed tooth representation to the final position model
generate a second 3D representation of the dentition comprising the plurality of teeth of the patient in the final position wherein generating the second 3D representation comprises:
apply the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position
Pavloskaia teaches:
receive a first 3D representation of a dentition comprising a plurality of teeth of a patient in an initial position (Pavloskaia; [Page 6, Line 15];” an initial digital data set (IDDS) representing an initial tooth arrangement is obtained (step 202).”), the first 3D representation comprising a plurality of tooth representations (Pavloskaia, [Page 9, Line 8; “Once a 3D model of the tooth surfaces has been constructed, models of the patient's individual teeth can be derived”)
determine tooth movements of the plurality of teeth of the dentition from the initial position to a final position (Pavloskaia, [Page 4, Line 28]; “moved from an initial tooth arrangement to a final tooth arrangement.”) based on applying each compressed tooth representation to the final position model (Pavlovskaia, [Page 2, Line 14]; “creating a parametric representation of the digital data set; and displaying the computer model of the teeth using the parametric representation. Implementations of the method include one or more of the following. The parametric representation is a compressed version of the digital data set.”)
generate a second 3D representation of the dentition comprising the plurality of teeth of the patient in the final position (Pavlovskaia, [Page 7 Line 20];” the final teeth arrangement is incorporated into a final digital data set (FDDS) (step 204)”), wherein generating the second 3D representation comprises:
apply the tooth movements to the first 3D representation of the detention comprising the plurality of teeth of the patient in the initial position (Pavlovskaia, [Page 7 Line 12]; “The IDDS is manipulated using a computer having a suitable graphical user interface (GUI) and software appropriate for viewing and modifying the images. More specific aspects of this process will be described in detail below. Individual tooth and other components may be segmented or isolated in the model to permit their individual repositioning or removal from the digital model. “)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li with Pavloskaia. The motivation for the combination is to be able create a second 3D representation of dentition by applying tooth movements to the first 3D representation (Pavlovskaia, [Page 9 Line 12];” Alternatively, the teeth may be repositioned based on the visual appearance or based on rules and algorithms programmed into the computer. Once an acceptable final arrangement has been created, the final tooth arrangement is incorporated into a final digital data set (FDDS).”)
Claims 3-5, 22-23 are rejected under 35 U.S.C. 103 as being unpatentable over Anssari (WO 2020048960 A1), LI (US 20210186659 A1) and Pavloskaia (WO0161613A1) further in view of Dean (US20210151172A1).
Regarding claim 3, the combination of Anssari, Li, and Pavloskaia fails to teach:
displaying, by the one or more processors, the treatment plan to a user of a user device, the treatment plan being a preliminary treatment plan.
Dean teaches:
displaying, by the one or more processors, the treatment plan to a user of a user device, the treatment plan being a preliminary treatment plan. (Dean, [0025]; “wherein creating the treatment plan comprises dynamically adjusting the treatment plan based on selections entered into the second device and based on data received from the first device”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia with Dean. The motivation for the combination is to be able allow the user to view the treatment plan. (Dean, [0063];” According to some embodiments, once a patient selects their payment choice, the treatment plan will be automatically updated on the web-based platform and the PMS.”)
arrangement has been created; the final tooth arrangement is incorporated into a final digital data set (FDDS).”)
Regarding claim 4, the combination of Anssari, Li, and Pavloskaia fails to teach:
receiving, by the one or more processors, from the user device, validation of the treatment plan based on an input received by the user device
Dean teaches:
receiving, by the one or more processors, from the user device, validation of the treatment plan based on an input received by the user device (Dean, [0051];” Consent forms can also be automatically communicated to a patient's device from the web-based platform, via a SMS or e-mail for example”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia with Dean. The motivation for the combination is to be able have the user validate and accept the treatment plan. (Dean, [Fig. 16], Informed consent page)
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Regarding claim 5, the combination of Anssari, Li, and Pavloskaia fails to teach:
further comprising booking, based on an interaction with the user device, an appointment with an office or order a product based on the displayed treatment plan.
Dean teaches:
further comprising booking (Dean,[0078];” the on-line scheduling features include schedule intelligence functions, such as nudge and cluster, which can manage appointments that are scheduled on-line in a manner that optimizes efficiency, meets doctor preferences, while being ideal for the dental practice and the patient.”), based on an interaction with the user device, an appointment with an office or order a product based on the displayed treatment plan (Dean, [0068];” when a dental patient purchases goods and/or services related to a dynamic treatment plan that has been automatically generated by the web-based platform, the application can also be used as the platform for billing and payment by the dental office”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia with Dean. The motivation for the combination is to be able have the user book an appointment with the office. (Dean, [FIGS. 66-68], FIGS. 66-68 illustrate examples of displayed screens from the web-based platform associated with an implemented on-line appointment scheduling feature, according to one or more embodiments shown and described herein)
Regarding claim 22, the combination of Anssari, Li, and Pavloskaia teaches:
generate a treatment plan based on the determined tooth movements of the plurality of teeth of the dentition; and (Pavlovskaia, [Page 4 Line 23]; “Systems and methods are provided for modeling teeth in creating a treatment plan.”) based on the determined tooth movements of the plurality of teeth of the dentition.)
The combination of Anssari, Li, and Pavloskaia fails to teach:
transmit the treatment plan to a user device thereby causing the treatment plan to be displayed on the user device.
Dean teaches:
transmit the treatment plan to a user device thereby causing the treatment plan to be displayed on the user device. (Dean, [0025]; “wherein creating the treatment plan comprises dynamically adjusting the treatment plan based on selections entered into the second device and based on data received from the first device
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li and Pavloskaia with Dean. The motivation for the combination is to be able allow the user to view the treatment plan. (Dean, [0063];” According to some embodiments, once a patient selects their payment choice, the treatment plan will be automatically updated on the web-based platform and the PMS.”)
Regarding claim 23, the combination of Anssari, Li, Pavloskaia and Dean teaches:
wherein generating the treatment plan comprises generating a plurality of intermediate 3D representations (Anssari, [0004];” In order to determine segmented paths (i.e. incremental movements to intermediate positions over time) for each of the teeth crowns, a finite element model of an in-place aligner is created and finite element analysis is applied.”) of the dentition showing a progression of the plurality of teeth from the initial position to the final position, wherein each of the plurality of intermediate 3D representations correspond to a respective stage of the treatment plan (Anssari, [004];” At various stages of the process, and in particular after the segmented paths have been defined, the process can, and generally will, interact with a clinician for the treatment of the patient.”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia and Dean. The motivation for the combination is to be able have a treatment with intermediate 3D representation. (Anssari, [0023], “Said at least one processor may be configured to determine said sequence of desired intermediate positions per tooth based on said determined desired final position”)
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Anssari (WO 2020048960 A1), Li (US 20210186659 A1) and Pavloskaia (WO0161613A1) further in view of Sepe (US7383198B1).
Regarding claim 6, the combination of Anssari, Li, and Pavloskaia fails to teach:
wherein the treatment plan is a final treatment plan, the final treatment plan being displayed, by the one or more processers, to a user of a user device.
Sepe teaches:
wherein the treatment plan is a final treatment plan, the final treatment plan being displayed, by the one or more processers, to a user of a user device. (Sepe, [Column 11 Line 10]; “The patient can also review the treatment plan and visualize the result using 3D imaging tools described above (step 292)”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia with Sepe. The motivation for the combination is to be able have the user view the treatment plan. (Sepe, [Column 2 Line 57], “The information associated with the patient's treatment (visual images, virtual treatment plans, file notes and the like) are digitized and maintained in a central storage facility in a secure manner. Doctors and patients can have access to these files without the need to extract files and models from storage and with reduced risk of records being misplaced.”)
Regarding claim 7, the combination of Anssari, Li, and Pavloskaia fails to teach:
further comprising displaying, by the one or more processers, an interactive button configured to initiate an order of a product based on the final treatment plan.
Sepe teaches:
further comprising displaying, by the one or more processers, an interactive button configured to initiate an order of a product based on the final treatment plan. (Sepe, [Column 5 Line 42];” Once the patient has accepted a particular treatment selection, the server 106 offers the patient with one or more financing options from one of its financial partners.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia with Sepe. The motivation for the combination is to be able have an interactive button for ordering. (Sepe, [Column 4 Line 29], “One partner 110 can be a financing partner that offers customers with one or more electronic financing options.”)
Regarding claim 8, the combination of Anssari, Li, and Pavloskaia fails to teach:
prompting, by the one or more processors, the user of the user device for patient information and product information.
Sepe teaches:
prompting, by the one or more processors, the user of the user device for patient information and product information. (Sepe, [Column 4 Line 39];” The customer enters the sensitive data such as credit card number, shipping address, among others, onto a purchase form.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia with Sepe. The motivation for the combination is to be able have the user input their info along with payment info. The user is able to provide previous dental images. (Sepe, [Column 12 Line 43], “Scanner 320 is responsible for scanning casts of the patient's teeth obtained either from the patient or from an orthodontist and providing the scanned digital data set information to data processing system 300 for further processing.”)
Claims 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Anssari (WO 2020048960 A1), LI (US 20210186659 A1) and Pavloskaia (WO0161613A1) further in view of Chekonin (US2020306011A1).
Regarding claim 11, the combination of Anssari, Li and Pavloskaia fails to teach:
further comprising, manufacturing a plurality of dental aligners specific to the detention and configured to move the plurality of teeth according to the determined tooth movements.
Chekonin teaches:
further comprising, manufacturing a plurality of dental aligners specific to the detention (Chekonin, [0035],” a method of manufacturing a series of aligners for a patient's teeth may include: collecting (e.g., receiving, forming, gathering, downloading, and/or accessing, from a remote site or a local site, and may be collected, for example, in a processor to be accessed by the user”) and configured to move the plurality of teeth according to the determined tooth movements. (Chekonin, [0007];” a dental aligner (e.g., a shell aligner) or other orthodontic device may be made to correspond to each stage”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia with Chekonin. The motivation for the combination is to be have dental aligner specific to the detention and move teeth according to the determined teeth movements. (Chekonin, [0342], “Thereafter the processor may receive preferences (e.g., interproximal reduction, attachments, tooth/teeth that don't move, etc.) specific to the patient treatment.”)
Regarding claim 12, the combination of Anssari, Li and Pavloskaia fails to teach
Chekonin teaches:
wherein manufacturing the plurality of dental aligners is based on receiving an approval from a user device. (Chekonin, [0242];” the user may then transmit the selected treatment plan to the manufacturer (technician) who may (optionally) review and send a finalized version of the treatment plan for final approval. Once approved, the treatment plan, including all of the stages of aligners, may be fabricated using the treatment plan either directly or converting it into a manufacturing format.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia with Chekonin. The motivation for the combination is to be have dental aligner approved by the user. (Chekonin; [0395];” In addition, the user interface may include one or more controls for modifying the treatment plan 4613. For example, the user may select ‘modify” and may use a tool to add/remove attachments 4607 and/or pontics, move the attachment, indicate IPR 4605, etc. Finally, if the treatment plan looks good, the user may indicate approval 4615 “)
Claims 24-25 are rejected under 35 U.S.C. 103 as being unpatentable over Anssari (WO 2020048960 A1), LI (US 20210186659 A1), Pavloskaia (WO0161613A1) and Dean (US20210151172A1) further in view of Chekonin (US20200306011A1).
Regarding claim 24, the combination of Anssari, Li, Pavloskaia, and Dean fails to teach:
further comprising, transmitting the treatment plan to a fabrication system configured to manufacture a plurality of dental aligners specific to the detention and configured to move the plurality of teeth according to the determined tooth movements.
Chekonin teaches:
further comprising, transmitting the treatment plan to a fabrication system (Chekonin, [0242];” may be fabricated using the treatment plan either directly or converting it into a manufacturing format.”) configured to manufacture a plurality of dental aligners specific to the detention (Chekonin, [0035],” a method of manufacturing a series of aligners for a patient's teeth may include: collecting (e.g., receiving, forming, gathering, downloading, and/or accessing, from a remote site or a local site, and may be collected, for example, in a processor to be accessed by the user”) and configured to move the plurality of teeth according to the determined tooth movement (Chekonin, [0007];” a dental aligner (e.g., a shell aligner) or other orthodontic device may be made to correspond to each stage”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia and Dean with Chekonin. The motivation for the combination is to be have dental aligner specific to the detention and move teeth according to the determined teeth movements. (Chekonin, [0342], “Thereafter the processor may receive preferences (e.g., interproximal reduction, attachments, tooth/teeth that don't move, etc.) specific to the patient treatment.”)
Regarding claim 25, the combination of Anssari, Li, Pavloskaia, and Dean fails to teach:
wherein transmitting the treatment plan to the fabrication system is based on receiving an approval from the user device.
Chekonin teaches:
wherein transmitting the treatment plan to the fabrication system is based on receiving an approval from the user device. (Chekonin, [0242];” the user may then transmit the selected treatment plan to the manufacturer (technician) who may (optionally) review and send a finalized version of the treatment plan for final approval. Once approved, the treatment plan, including all of the stages of aligners, may be fabricated using the treatment plan either directly or converting it into a manufacturing format.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Anssari, Li, Pavloskaia and Dean with Chekonin. The motivation for the combination is to be have dental aligner approved by the user. (Chekonin; [0395];” In addition, the user interface may include one or more controls for modifying the treatment plan 4613. For example, the user may select ‘modify” and may use a tool to add/remove attachments 4607 and/or pontics, move the attachment, indicate IPR 4605, etc. Finally, if the treatment plan looks good, the user may indicate approval 4615 “)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHIVANGI SARKAR whose telephone number is (571)272-7262. The examiner can normally be reached M-F: 7:30-5:00.
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/SHIVANGI SARKAR/Examiner, Art Unit 2666
/EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666