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 .
Response to Amendment
1 This action is in response to the amendment filed on 07/16/2026. Claims 1, 8-12, and 29-30 have been amended, and claim 7 has been cancelled. Claim 29 was also amended to overcome an objection. Claims 1-6 and 8-30 remain rejected.
Response to Arguments
2 Applicant’s arguments with respect to claims 1 and 29-30 filed on 07/16/2026, with respect to the rejection under 35 U.S.C. § 103 regarding that the prior art does not teach the following but not limited to “…determining a location of a virtual camera and a location of a projection plane associated with the virtual camera in 3D space with respect to a position of the 3D alignment model, wherein the location of the virtual camera establishes a 3D relationship between the 3D alignment model and the projection plane…”. Some elements of claim 7 were added to this claim therefore cancelling the claim, but the changes were enough to make the amendments be new grounds. This argument has been considered, but are moot due to new grounds of rejection.
3 Regarding claims 2-6 and 8-28, they directly/indirectly depend on independent claim 1 respectively. Applicant does not argue anything other than independent claims 1 and 29-30. The limitations in those claims, in conjunction with combination, was mostly previously established as explained, with some changes based on the independent claim changes.
4 Claim 7 as previously mentioned has been cancelled. Therefore, the claim will not be reviewed further. In addition to this removal, claim 21 is now considered to be a duplicate of claim 12 due to both being dependent of claim 1.
Claim Objections
5 Applicant is advised that should claim 12 be found allowable, claim 21 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim Rejections - 35 USC § 103
6 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
7 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.
8 Claim(s) 1, 5, 10, 12-22, 24, 28, and 30 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chernov et al. (US 20220165388 A1) in view of Karanam et al. (US 20230132479 A1) and Liu et al. (US 20080318179 A1).
9 Regarding claim 1, Chernov teaches a method comprising: generating a three-dimensional (3D) alignment model based on a patient’s 3D dental scans, wherein the 3D alignment model includes segmentation data of the patient’s upper jaw portion and lower jaw portion ([0104] reciting “The feature alignment engine 178 may implement one or more automated agents configured to align and merge segmented scan data from the scan segmentation engine(s) 160 with a digital 3D dental treatment plan. A digital 3D dental treatment plan may be generated during the course of a dental treatment for a patient. The dental treatment plan can comprise a three-dimensional model, such as a 3D mesh model or a 3D point cloud, that may be generated from a scan, such as an intraoral scan, of the patient's teeth.”; [0018] reciting “Automatically segmenting the 3D scan may further comprise: downsampling the 3D scan to a lower resolution than the 3D scan; segmenting the downsampled 3D scan with a first neural network to identify the patient's teeth, the patient's upper jaw bones, and the patient's lower jaw bones;”);
generating a two-dimensional (2D) alignment based on projecting the 3D alignment model ([0072] reciting “The results may include 3D virtual representations of the dental arch, 2D images or renditions of the dental arch, etc.”; [0073] reciting “The 3D segmentation system can be configured to input one or more different areas of the 2D scan, 3D scan, or 3D model into a machine learning model to automatically segment the scan or model into individual dental components, including segmenting the scan or model into individual teeth, bones, interproximal spaces between teeth, and/or gingiva.”);
10 Chernov does not explicitly teach determining a location of a virtual camera and a location of a projection plane associated with the virtual camera in 3D space with respect to a position of the 3D alignment model, wherein the location of the virtual camera establishes a 3D relationship between the 3D alignment model and the projection plane; generating a two-dimensional (2D) alignment projection based on projecting the 3D alignment model onto the projection plane; determining a 2D difference between a patient’s 2D dental image and the 2D alignment projection; and importing dental information from the patient’s 3D dental scan to the patient’s 2D dental image when the difference is less than a threshold.
11 Karanam teaches determining a location of a virtual camera and a location of a projection plane associated with the virtual camera in 3D space with respect to a position of the 3D alignment model, wherein the location of the virtual camera establishes a 3D relationship between the 3D alignment model and the projection plane ([0022] reciting “based on the 3D human model, whether the position and/or pose of the patient 106 meets the requirements of a predetermined protocol (e.g., while the patient 106 is standing in front of the medical scanner 102 or lying on a scan bed), and provide real-time confirmation or adjustment instructions (e.g., via the display device 112), to help the patient 106 get into the desired position and/or pose.”; [0031] reciting “Using the mapping relationship, a plurality of 3D key body locations may be determined based on the vertices of the 3D model 302 and the 3D key body locations may be projected into a 2D image frame (e.g., using predetermined camera and/or projection parameters) to obtain the set of key point locations. Similarly, given the vertices of the 3D human model 302, a shape outline of the person may also be obtained, for example, using the predetermined camera and/or projection parameters.”);
generating a two-dimensional (2D) alignment projection based on projecting the 3D alignment model onto the projection plane ([0022] reciting “For instance, the processing device 108 may align scan images of the patient 106 from the repository 114 with the 3D human model to allow the scan images to be presented (e.g., via display device 112) and analyzed with reference to the anatomical characteristics (e.g., body shape and/or pose) of the patient 106 as indicated by the 3D human model.”; [0031] reciting “Using the mapping relationship, a plurality of 3D key body locations may be determined based on the vertices of the 3D model 302 and the 3D key body locations may be projected into a 2D image frame (e.g., using predetermined camera and/or projection parameters) to obtain the set of key point locations. Similarly, given the vertices of the 3D human model 302, a shape outline of the person may also be obtained, for example, using the predetermined camera and/or projection parameters.”);
12 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov) to incorporate the teachings of Karanam to provide a method to include a location of a type of virtual camera and a projection plane (a 2d area) for the 3d space in the 3d alignment model including their relationships and types of projections, utilizing the models provided by Chernov. Doing so would allow the images to be analyzed with reference to the anatomical characteristics as stated by Karanam ([0022] recited).
13 Chernov in view of Karanam does not explicitly teach determining a 2D difference between a patient’s 2D dental image and the 2D alignment projection; and importing dental information from the patient’s 3D dental scan to the patient’s 2D dental image when the difference is less than a threshold.
14 Liu teaches determining a 2D difference between a patient’s 2D dental image and the 2D alignment projection ([0042] reciting “In this embodiment, one (or preferably more) 2D images of the current dental arch or a portion of the current dental arch (e.g., picture of ill-fitting region) are provided (see 300 in FIG. 3) and can be used to correct the position of the subject's teeth. For example, the dentist or practitioner may provide images (including x-rays, photographs, etc.) of the subject's teeth. The digital model of the subject's teeth (the model to be corrected, 301) may then be compared to these images (302), and the difference between the actual tooth position shown in the images (or scans) and the digital model may be calculated.”);
and importing dental information from the patient’s 3D dental scan to the patient’s 2D dental image when the difference is less than a threshold ([0045] reciting “Also as described above for the 3D scanning technique, the accuracy of the position of the corrected dental arch tooth models may be checked (304). For example, surface area subtraction may be done to determine if the difference between the corrected model and the image(s) provided falls within an acceptable range. Thus, 2D projections from the digital dental arch model may be generated in the same perspective as the provided image(s), and the edges of the surfaces compared. Differences in the two surfaces (e.g., where they do not align) may be determined, and compared to a threshold value. As mentioned above, a threshold error may be set (e.g., less than 5%, less than 1%,less than 0.5%, less than 0.1%, less than 0.05%, less than 0.01%, or some intermediate value), and an error exceeding this threshold results in a "failure" of the correction technique.”).
15 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam) to incorporate the teachings of Liu to provide methods that determine a type of difference between a dental image and the alignment model, as well as to import the dental information when the difference is less than a threshold utilizing the various dental images and alignment models provided by the teachings of Chernov in view of Karanam. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
16 Regarding claim 5, Chernov in view of Karanam and Liu teaches the method of claim 1, wherein generating the 3D alignment model includes moving the lower jaw portion with respect to the upper jaw portion (Chernov; [0018] reciting “downsampling the 3D scan to a lower resolution than the 3D scan; segmenting the downsampled 3D scan with a first neural network to identify the patient's teeth, the patient's upper jaw bones, and the patient's lower jaw bones; performing a center of teeth area computation to determine where the patient's teeth are positioned within the 3D scan;”).
17 Regarding claim 10, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claims 1 rejection above),
18 Karanam as previously mentioned in claim 1 can further teach parts of the limitation, specifically the projection plane ([0022] reciting “For instance, the processing device 108 may align scan images of the patient 106 from the repository 114 with the 3D human model to allow the scan images to be presented (e.g., via display device 112) and analyzed with reference to the anatomical characteristics (e.g., body shape and/or pose) of the patient 106 as indicated by the 3D human model.”; [0031] reciting “Using the mapping relationship, a plurality of 3D key body locations may be determined based on the vertices of the 3D model 302 and the 3D key body locations may be projected into a 2D image frame (e.g., using predetermined camera and/or projection parameters) to obtain the set of key point locations. Similarly, given the vertices of the 3D human model 302, a shape outline of the person may also be obtained, for example, using the predetermined camera and/or projection parameters.”)…
19 As explained in the rejection of claim 1, the obviousness for combining of the projection plane of Karanam into Chernov (and by extension Liu) is provided above.
20 Liu from claim 1 can further teach the limitations, specifically wherein a portion of the projection plane is cropped prior to determining 2D differences between the patient’s 2D dental image and the 2D alignment projection. ([0042] reciting “In this embodiment, one (or preferably more) 2D images of the current dental arch or a portion of the current dental arch (e.g., picture of ill-fitting region) are provided (see 300 in FIG. 3) and can be used to correct the position of the subject's teeth. For example, the dentist or practitioner may provide images (including x-rays, photographs, etc.) of the subject's teeth. The digital model of the subject's teeth (the model to be corrected, 301) may then be compared to these images (302), and the difference between the actual tooth position shown in the images (or scans) and the digital model may be calculated.”) (Chernov; [0074] reciting “The scan segmentation engine(s) 160 of the 3D segmentation system 158 may implement automated agents to process 2D or 3D scans taken by the scanning system 154. In some implementations, the scan segmentation engine(s) 160 formats scan data from a scan of a dental arch into one or more partitions, volumes, crops, or areas of the scan.) (Boltunov; [0070] reciting “Points (e.g., x points) can be marked on a same position on the patient's jaws in each photograph. Corresponding X points can be marked on the 3D digital dental model 651. The X points can be fit to a common plane p as Y points.”; [0081] reciting “As described herein, a jaw of the digital dental model can be segmented into a number of teeth (e.g., where each tooth is defined by a closed mesh).”).
21 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate additional teachings of Liu to provide a method the crops a type of projection plane (2d flat image) with the data containing the differences, utilizing the alignment projections provided by Chernov in view of Karanam and Liu. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
22 Regarding claim 12, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above),
23 Karanam as previously mentioned in claim 1 can further teach parts of the limitation, specifically the projection plane ([0022] reciting “For instance, the processing device 108 may align scan images of the patient 106 from the repository 114 with the 3D human model to allow the scan images to be presented (e.g., via display device 112) and analyzed with reference to the anatomical characteristics (e.g., body shape and/or pose) of the patient 106 as indicated by the 3D human model.”; [0031] reciting “Using the mapping relationship, a plurality of 3D key body locations may be determined based on the vertices of the 3D model 302 and the 3D key body locations may be projected into a 2D image frame (e.g., using predetermined camera and/or projection parameters) to obtain the set of key point locations. Similarly, given the vertices of the 3D human model 302, a shape outline of the person may also be obtained, for example, using the predetermined camera and/or projection parameters.”)…
24 As explained in the rejection of claim 1, the obviousness for combining of the projection plane of Karanam into Chernov (and by extension Liu) is provided above.
25 Liu from claim 1 can further teach the limitations, specifically wherein generating the 2D alignment projection includes iteratively determining a position of the projection plane based on the difference between the patient’s 2D dental image and the 2D alignment projection ([0043] reciting “Using the digital model, the teeth position are iteratively examined (e.g., through each projection of the teeth), and edge matching can be used to subtract the difference between individual tooth in the actual position of the dental arch with the corresponding teeth positioned in the 2D image projection from the model.”).
26 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate additional teachings of Liu to provide a method that can iteratively determine a position of the plane (2d flat image) based on the differences, utilizing the alignment projections provided by Chernov in view of Karanam and Liu. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
27 Regarding claim 13, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), wherein the 2D dental image is based on a photo of the patient’s dentition (Chernov; [Abstract] reciting “A patient's dentition may be scanned with a 3D scanning system, such as CT, CBCT, or MRI. The 3D scan data may be automatically segmented with one or more neural networks. The segmented 3D scan can be incorporated into a dental treatment plan.”; [0071] reciting “In other implementations the scanning system 154 is configured to produce 2D scans or images of the patient's dentition.”).
28 Regarding claim 14, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), wherein the 2D dental image includes 2D information of an upper jaw portion and a lower jaw portion (Chernov; [0084] reciting “The image processing engine 170 may implement one or more automated agents configured to format 2D or 3D scan data from a scan of a dental arch scan data into one or more partitions, volumes, crops, or areas of the scan. For example, the image processing engine may receive or access a 3D scan of a patient's dentition, such as a CT scan, a CBCT scan, or a MRI scan, which can include high-resolution imaging data of the patient's dental features, including the patient's teeth and the upper and lower bones of the patient's jaw.”).
29 Regarding claim 15, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above),
30 Liu from claim 1 can further teach the limitations, specifically wherein determining the 2D differences between the patient’s 2D dental image and the 2D alignment projection includes determining a difference between corresponding features of the patient’s 2D dental image and the 2D alignment projection ([0038] reciting “The difference in teeth position between the actual arrangement and the modeled arrangement of the subject's dental arch may be calculated by determining the difference in position of each tooth within the dental arch between the two, and calculating the offset in each tooth of the arch.”).
31 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate additional teachings of Liu to provide a type of general difference between certain dental images and types of alignments and including their features, utilizing the alignment projections provided by Chernov in view of Karanam and Liu. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
32 Regarding claim 16, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above),
33 Liu from claim 1 can further teach the limitations, specifically wherein the determining the 2D differences between the patient’s 2D dental image and the 2D alignment projection includes determining a difference between outlines of corresponding dental structures of the patient’s 2D dental image and the 2D alignment projection ([Abstract] reciting “A method of correcting a dental arch model so that it accurately reflects the current arrangement of a subject's teeth includes positioning a plurality of tooth models in a corrected arrangement using a representation of at least a portion of a subject's current dental arch (wherein the tooth models comprise models of the subject's teeth having fiduciary markers), and producing a base plate configured to hold the plurality of tooth models in the corrected arrangement. The representation of the current arrangement may be, for example, a physical impression of the subject's teeth, a 3D scan or one or more 2D scans of the subject's teeth.”; [0042] reciting “In this embodiment, one (or preferably more) 2D images of the current dental arch or a portion of the current dental arch (e.g., picture of ill-fitting region) are provided (see 300 in FIG. 3) and can be used to correct the position of the subject's teeth. For example, the dentist or practitioner may provide images (including x-rays, photographs, etc.) of the subject's teeth. The digital model of the subject's teeth (the model to be corrected, 301) may then be compared to these images (302), and the difference between the actual tooth position shown in the images (or scans) and the digital model may be calculated.”).
34 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate additional teachings of Liu to provide a type of difference for outlines between certain dental images and types of alignments and including their features, utilizing the alignment projections provided by Chernov in view of Karanam and Liu. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
35 Regarding claim 17, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above),
36 Liu from claim 1 can further teach the limitations, specifically wherein the determining the difference between the patient’s 2D dental image and the 2D alignment projection includes determining a difference between tooth boundaries determined from the patient’s 2D dental image and the 2D alignment projection ([0042] reciting “In this embodiment, one (or preferably more) 2D images of the current dental arch or a portion of the current dental arch (e.g., picture of ill-fitting region) are provided (see 300 in FIG. 3) and can be used to correct the position of the subject's teeth. For example, the dentist or practitioner may provide images (including x-rays, photographs, etc.) of the subject's teeth. The digital model of the subject's teeth (the model to be corrected, 301) may then be compared to these images (302), and the difference between the actual tooth position shown in the images (or scans) and the digital model may be calculated.”).
37 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate additional teachings of Liu to provide a type of difference based on tooth boundaries between certain dental images and types of alignments and including their features, utilizing the alignment projections provided by Chernov in view of Karanam and Liu. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
38 Regarding claim 18, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), wherein the segmentation data is generated with one or more machine learning engines and one or more 3D models (Chernov; [0006] reciting “The present application addresses these and other technical problems by providing technical solutions and/or automated agents that automatically segment teeth and dental features using machine learning neural networks. In some implementations, segmentation of 3D datasets is performed with a set of 3D convolutional neural networks that processes different areas of the 3D dataset with different volumetric resolutions.”).
39 Regarding claim 19, Chernov in view of Karanam and Liu teaches the method of claim 1, wherein the dental information includes tooth number information (Chernov; [0099] reciting “For multi-class teeth segmentation, every voxel belonging to the dedicated tooth is labeled by the system with its tooth number value and all other voxels are labeled with a value ‘0’ (e.g., so the system assigns labels with values 0-32).”).
40 Regarding claim 20, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above),
41 Liu from claim 1 can further teach the limitations, specifically wherein generating the 3D alignment model further comprises iteratively determining a position of the lower jaw portion with respect to the upper jaw portion based on the difference between the patient’s 2D dental image and the 2D alignment projection ([0043] reciting “Using the digital model, the teeth position are iteratively examined (e.g., through each projection of the teeth), and edge matching can be used to subtract the difference between individual tooth in the actual position of the dental arch with the corresponding teeth positioned in the 2D image projection from the model.”).
42 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate additional teachings of Liu to provide a method that determines positions of a jaw on both ends based on the differences, utilizing the alignment projections provided by Chernov in view of Karanam and Liu. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
43 Regarding claim 21, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above),
44 Karanam as previously mentioned in claim 1 can further teach parts of the limitation, specifically the projection plane ([0022] reciting “For instance, the processing device 108 may align scan images of the patient 106 from the repository 114 with the 3D human model to allow the scan images to be presented (e.g., via display device 112) and analyzed with reference to the anatomical characteristics (e.g., body shape and/or pose) of the patient 106 as indicated by the 3D human model.”; [0031] reciting “Using the mapping relationship, a plurality of 3D key body locations may be determined based on the vertices of the 3D model 302 and the 3D key body locations may be projected into a 2D image frame (e.g., using predetermined camera and/or projection parameters) to obtain the set of key point locations. Similarly, given the vertices of the 3D human model 302, a shape outline of the person may also be obtained, for example, using the predetermined camera and/or projection parameters.”)…
45 As explained in the rejection of claim 1, the obviousness for combining of the projection plane of Karanam into Chernov (and by extension Liu) is provided above.
46 Liu from claim 1 can further teach the limitations, specifically wherein generating the 2D alignment projection includes iteratively determining a position of a projection plane based on the difference between the patient’s 2D dental image and the 2D alignment projection ([0043] reciting “Using the digital model, the teeth position are iteratively examined (e.g., through each projection of the teeth), and edge matching can be used to subtract the difference between individual tooth in the actual position of the dental arch with the corresponding teeth positioned in the 2D image projection from the model.”).
47 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate additional teachings of Liu to provide a method that can iteratively determine a position of the plane (2d flat image) based on the differences, utilizing the alignment projections provided by Chernov in view of Karanam and Liu. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
48 Regarding claim 22, Chernov in view of Karanam and Liu teaches the method of claim 1, further comprising: generating a 3D image based on the 2D alignment projection (Chernov; [0066] reciting “As described herein, an intraoral scanner may image a patient's dental arch and generate a virtual three-dimensional model of that dental arch.”; [0104] reciting “The feature alignment engine 178 may implement one or more automated agents configured to align and merge segmented scan data from the scan segmentation engine(s) 160 with a digital 3D dental treatment plan. A digital 3D dental treatment plan may be generated during the course of a dental treatment for a patient.”).
49 Regarding claim 24, Chernov in view of Karanam and Liu teaches the method of claim 1, wherein the patient’s 3D dental scans are associated with a previously determined treatment plan (Chernov; [0071] reciting “The scanning system 154 may be used as part of an orthodontic treatment plan. In some implementations, the scanning system 154 is configured to capture a patient's dental arch at a beginning stage, an intermediate stage, etc. of an orthodontic treatment plan. The scanning system 154 may be further configured to receive 2D or 3D scan data taken previously or by another system.”).
50 Regarding claim 28, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), further comprising determining or correcting tooth numbering using the patient’s 3D dental scan (Chernov; [0031] reciting “…stitching teeth crowns from the virtual treatment plan to corresponding teeth roots from the segmented 3D scan data; and numbering individual segmented teeth in the virtual treatment plan.”).
51 Claim 30 has similar limitations as of claim 1, therefore it is rejected under the same rationale as claim 1.
52 Claim(s) 2-3, 8, and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chernov et al. (US 20220165388 A1) in view of Karanam et al. (US 20230132479 A1) and Liu et al. (US 20080318179 A1) as of claim 1, further in view of Boltunov et al. (US 20110045428 A1).
53 Regarding claim 2, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), and although could teach wherein generating the 3D alignment model includes determining a position of the lower jaw portion with respect to the upper jaw portion (Chernov; [0018] reciting “downsampling the 3D scan to a lower resolution than the 3D scan; segmenting the downsampled 3D scan with a first neural network to identify the patient's teeth, the patient's upper jaw bones, and the patient's lower jaw bones; performing a center of teeth area computation to determine where the patient's teeth are positioned within the 3D scan”), prior art from Boltunov can teach this limitation further.
54 Boltunov teaches wherein generating the 3D alignment model includes determining a position of the lower jaw portion with respect to the upper jaw portion ([0026] reciting “At 205, software can set initial positions of the digital model of the patient's jaws. When the scans of the physical dental molds are segmented into a number of teeth, a relational correspondence between teeth in the upper jaw and lower jaw of the digital dental model can be determined.”; [0050] reciting “As described herein, data comprising the upper jaw 653 and the lower jaw 655 may be obtained independently of each other and/or without information about relative positions of the upper jaw 653 and the lower jaw 655 in a bite configuration. Mapping information about the patient's jaws in a bite configuration (e.g., from a photograph thereof) can aid in bite setting the 3D digital dental model 651.”).
55 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Boltunov to provide a clearer method that determine a position of the upper and lower jaws that are provided by the teachings of Chernov in view of Karanam and Liu. Doing so would aid in accurately positioning the upper jaw and the lower jaw in a bite configuration as stated by Boltunov ([0050] recited).
56 Regarding claim 3, Chernov in view of Karanam, Liu, and Boltunov teaches the method of claim 2 (see claims 1-2 rejections above),
57 Boltunov from claim 2 can further teach the limitations, specifically wherein the position of the lower jaw portion is constrained by a location of a joint coupling the lower jaw portion to the upper jaw portion [0028] reciting “As used herein, a fixed jaw of the digital dental model is a jaw that has one or more degrees of freedom constrained within the model (e.g., all six degrees of freedom can be constrained for the fixed jaw).”).
58 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam, Liu, and Boltunov) to incorporate additional teachings of Boltunov to provide the position of a lower jaw to be constrained by a location of a joint coupling both jaws, utilizing the jaw data provided by Chernov in view of Karanam, Liu, and Boltunov. Doing so would aid in accurately positioning the upper jaw and the lower jaw in a bite configuration as stated by Boltunov ([0050] recited).
59 Regarding claim 8, Chernov in view of Karanam and Liu teaches the method of claim 1, further comprising (see claim 1 rejection above): but does not explicitly teach projecting dental elements from the 3D alignment model to the projection plane, wherein the 2D alignment projection is based on the projected dental elements.
60 Boltunov teaches ([0045] reciting “Points denoted "Y" represent X points fit to a common plane p (e.g., projected onto plane p), as described herein. That is, X points marked on the 3D digital dental model may not inherently fit a common plane because they are marked in a 3D coordinate system. However, according to one or more embodiments of the present disclosure, X points can be projected to a common plane "p," and after which are denoted as Y points (e.g., a change in 3D coordinates for a particular X point may occur when the particular X point is projected to the plane p).”; [0062] reciting “Thus, the camera can be approximated with a composition of the projection .pi. and a projective 2D to 2D transformation G.”; [0124] reciting “As described herein the plurality of G.sup.-1(x) points can be mapped to the 3D digital dental model by transforming a coordinate system of the 2D data to a coordinate system of the 3D data set.”).
61 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Boltunov to provide a type of projection of dental elements with the 2D projection being based on the dental elements that can be provided by the teachings of Chernov in view of Karanam and Liu. Doing so would aid in accurately positioning the upper jaw and the lower jaw in a bite configuration as stated by Boltunov ([0050] recited).
62 Regarding claim 11, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), but does not explicitly teach wherein determining the location of the 3D alignment model includes locating the patient’s upper jaw portion in 3D space using six degrees of freedom and locating the patient’s lower jaw portion in the 3D space using one degree of freedom.
63 Boltunov teaches wherein determining the location of the 3D alignment model includes locating the patient’s upper jaw portion in 3D space using six degrees of freedom and locating the patient’s lower jaw portion in the 3D space using one degree of freedom ([0028] reciting “During simulation of movement, if the two jaws have not come into contact from their initial positions, then there would be zero reaction force acting on the digital dental model. As used herein, a fixed jaw of the digital dental model is a jaw that has one or more degrees of freedom constrained within the model (e.g., all six degrees of freedom can be constrained for the fixed jaw).”).
64 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Boltunov to provide a method that determines a location of a jaw utilizing the six degrees of freedom and using those degrees to locate a jaw with the jaw data provided by Chernov in view of Karanam and Liu. Doing so would aid in accurately positioning the upper jaw and the lower jaw in a bite configuration as stated by Boltunov ([0050] recited).
65 Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chernov et al. (US 20220165388 A1) in view of Liu et al. (US 20080318179 A1), Karanam et al. (US 20230132479 A1), and Boltunov et al. (US 20110045428 A1) as of claims 1-2, further in view of Malfliet et al. (US 20110191081 A1).
66 Regarding claim 4, Chernov in view of Karanam, Liu, and Boltunov teaches the method of claim 2 (see claims 1-2 rejections above), but does not explicitly teach wherein the position of the lower jaw portion is determined, at least in part, by a temporomandibular joint disposed with respect to the upper jaw portion.
67 Malfliet teaches wherein the position of the lower jaw portion is determined, at least in part, by a temporomandibular joint disposed with respect to the upper jaw portion ([0039] reciting “The absolute positioning is meant to transfer the relation between the condyles and the maxilla from the patient to the articulator so that the model of the upper dentition is located in the same three-dimensional position with respect to the condylar replications on the articulator.”; [0016] reciting “A virtual articulator is used to determine the impact of a proposed dental modification on the temporomandibular joint(s). An articulator is a mechanical instrument, which is used to examine the static and dynamic contact relationships between the occlusal surfaces of both dental arches. It mimics the human temporomandibular joints and jaws and consists of an upper and a lower member to which maxillary and mandibular casts may be attached in order to simulate some or all mandibular movements.”).
68 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam, Liu, and Boltunov) to incorporate the teachings of Malfliet to provide a method that can provide a specific TMJ for the specific jaws for the 3d alignment methods that are taught by the teachings of Chernov in view of Karanam, Liu, and Boltunov. Doing so would allow dental modifications like the replacement of one or more teeth by artificial teeth, the replacement of one or more parts of a tooth by a prosthetic reconstruction such as a dental crown or veneer, the rearrangement of one or more existing teeth (orthodontic treatment), the distraction of one or both jaws in order to reposition the teeth (orthognatic treatment) and/or modifications of the occlusal surfaces of the teeth as stated by Malfliet ([Abstract] recited).
69 Claim(s) 6 and 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chernov et al. (US 20220165388 A1) in view of Karanam et al. (US 20230132479 A1) and Liu et al. (US 20080318179 A1) as of claims 1 and 5, further in view of Chun et al. (US 20140287379 A1).
70 Regarding claim 6, Chernov in view of Karanam and Liu teaches the method of claim 5 (see claims 1 and 5 rejections above), but does not explicitly teach wherein moving the lower jaw portion is based on a location of a joint coupling the lower jaw portion to the upper jaw portion.
71 Chun teaches wherein moving the lower jaw portion is based on a location of a joint coupling the lower jaw portion to the upper jaw portion ([0008] reciting “In an embodiment, the bite frame further comprises radio-opaque markers positioned at predetermined locations along an inner rim of the arcuate frame element. The radio-opaque markers provide reference points to positions of the upper jaw and the lower jaw in two-dimensional (2D) panoramic X-ray images of the upper jaw and the lower jaw, a three-dimensional (3D) panoramic X-ray image created using the 2D panoramic X-ray images of the upper jaw and the lower jaw, and 3D scanned images of the bite impression for the determination of the 3D relation between the upper jaw and the lower jaw.”).
72 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Chun to provide a method that determines when a jaw portion is moved based on a specific joint coupling, utilizing the jaw portions that are provided by the teachings of Chernov in view of Karanam and Liu. Doing so would allow a bite registration apparatus comprising the bite frame and the bite shaped member of one of multiple flexible geometric shapes for registering a bite impression as stated by Chun ([0016] recited).
73 Regarding claim 23, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), and although could teach wherein the patient’s 2D dental image is a closed-bite photo (Chernov; see Fig. 3c), prior art from Chun can teach this limitation further.
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74 Chun teaches wherein the patient’s 2D dental image is a closed-bite photo ([0060] reciting “For a patient with natural dentition, a closed bite frame 300 with a wide arcuate or arch opening 304 filled with the mesh element 303 is used. The mesh element 303 is configured to receive a bite registration material for registering a bite impression comprising an impression of the upper jaw and an impression of the lower jaw, and thereafter enabling the determination of the 3D relation between the upper jaw and the lower jaw.”).
75 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Chun to provide a clearer method that the dental image provided by the teachings of Chernov in view of Karanam and Liu to be a closed-bite photo. Doing so would comprise an impression of the upper jaw and an impression of the lower jaw, and thereafter enabling the determination of the 3D relation between the upper jaw and the lower jaw as stated by Chun ([0060] recited).
76 Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chernov et al. (US 20220165388 A1) in view of Karanam et al. (US 20230132479 A1) and Liu et al. (US 20080318179 A1) as of claims 1, further in view of Elazar et al. (US 20190015177 A1).
77 Regarding claim 9, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), but does not explicitly teach wherein the location of the 3D alignment model and the location of the projection plane is based, at least in part, on a point-of-view associated with a virtual camera disposed in the common virtual 3D space.
78 Elazar teaches wherein the location of the 3D alignment model and the location of the projection plane is based, at least in part, on a point-of-view associated with a virtual camera disposed in the common virtual 3D space ([0059] reciting “A 3D model of the bracket from the library is then superimposed onto the viewport space of the immersive photographic model.”; [0072] reciting “A health care provider may then choose to “rotate” the camera around the center point, rotating the viewport as well for displaying various angles of the mouth around the same center point. When the virtual camera changes perspective, a different sphere is selected or a different portion of the sphere is mapped to viewport 104, resulting in rendering a different subject matter from the immersive photography model.”; [0159] reciting “The horizontal axis is selected to be parallel to the horizontal plane of the reference 3D space, which, for example, may be parallel to the base of the virtual camera.”).
79 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Elazar to provide a virtual camera for a type of point-of-view setting in a virtual 3d space that is provided by the teachings of Chernov in view of Karanam and Liu. Doing so would allow a horizontal plane of the reference 3D space, which, for example, may be parallel to the base of the virtual camera as stated by Elazar ([0159] recited).
80 Claim(s) 25-27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chernov et al. (US 20220165388 A1) in view of Karanam et al. (US 20230132479 A1) and Liu et al. (US 20080318179 A1) as of claim 1, further in view of Layzell et al. (US 20160158627 A1).
81 Regarding claim 25, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection above), but does not explicitly teach wherein importing dental information from the patient’s 3D dental scan comprises determining a bite class from the 3D dental scan.
82 Layzell teaches wherein importing dental information from the patient’s 3D dental scan comprises determining a bite class from the 3D dental scan ([0067] reciting “FIGS. 32A-32C show which of the dental impression bite registration bite forks in FIGS. 30 and 31A and/or which orientation of the dental impression bite registration bite fork in FIGS. 31A and 31B to use for a particular bite class of a user.”; [0125] reciting “The patentee has developed a unique X-Y-Z quadrant fitting system that pinpoints each athlete's or user's unique vertical, horizontal, and sagittal mandible position. This unique 3-dimensional position can then be used to create a customized occlusal opening and jaw position that naturally and symmetrically aligns the jaw for optimized respiratory, skeletal, muscular, physiological, and neurological function.”).
83 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Layzell to provide a specific bite class for the 3D dental scans that are provided by the teachings of Chernov in view of Karanam and Liu. Doing so would allow to create a customized occlusal opening and jaw position that naturally and symmetrically aligns the jaw for optimized respiratory, skeletal, muscular, physiological, and neurological function as stated by Layzell ([0125] recited).
84 Regarding claim 26, Chernov in view of Karanam, Liu, and Layzell teaches the method of claim 25 (see claims 1 and 25 rejections above), wherein determining the bite class from the 3D dental scan comprises identifying one or more of: class I malocclusion, class II malocclusion, class III malocclusion, crossbite, deep bite, and/or open bite.
85 Layzell from claim 25 can further teach the limitation, specifically wherein determining the bite class from the 3D dental scan comprises identifying one or more of: class I malocclusion, class II malocclusion, class III malocclusion, crossbite, deep bite, and/or open bite ([0132] reciting “The dental impression bite registration bite fork 170 is configured to accommodate more severe overbite and underbite malocclusal classes, i.e., Class II/Class III malocclusal conditions.”).
86 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam, Liu, and Layzell) to incorporate additional teachings of Layzell to provide a different type of bite class from a 3D dental scan that is provided by Chernov in view of Karanam, Liu, and Layzell. Doing so would allow to create a customized occlusal opening and jaw position that naturally and symmetrically aligns the jaw for optimized respiratory, skeletal, muscular, physiological, and neurological function as stated by Layzell ([0125] recited).
87 Regarding claim 27, Chernov in view of Karanam and Liu teaches the method of claim 1 (see claim 1 rejection), and although could teach further comprising measure a degree of malocclusion from the patient’s 3D dental scan (Chernov; [0006] reciting “Automatic tooth segmentation may provide the basis for implementation of automated orthodontic treatment plans, design and/or manufacture of orthodontic aligners (including series of polymeric orthodontic aligners that provide forces to correct malocclusions in patients' teeth).”), prior art from Layzell can teach this limitation further.
88 Layzell teaches further comprising measure a degree of malocclusion from the patient’s 3D dental scan ([0143] reciting “The user or subject may be instructed to pull the dental impression bite registration tool F forward slightly and keep it level during this step in order to correctly position the 3-dimensional bite position.”; [0159] reciting “The tooth positioners 186, 188 on the Class I dental impression bite registration bite fork 160 are vertically aligned, as noted above. The tooth positioners 186, 188 on the Class II/III bite fork (FIGS. 42a, 42b) are offset to accommodate a larger degree of malocclusion, also as noted above.”).
89 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Layzell to provide a clearer method that can measure a degree of malocclusion based on the malocclusion data and the 3D dental scan provided by the teachings of Chernov in view of Karanam and Liu. Doing so would add structural integrity and stiffness to the bite fork as stated by Layzell ([0159] recited).
90 Claim(s) 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chernov et al. (US 20220165388 A1) in view of Karanam et al. (US 20230132479 A1), Liu et al. (US 20080318179 A1), and Malfliet et al. (US 20110191081 A1).
91 Regarding claim 29, Chernov teaches a method comprising: generating or accessing a three-dimensional (3D) alignment model of a digital model of a patient’s upper jaw portion and a digital model of the patient’s lower jaw portion, wherein the digital model of the patient’s upper jaw portion and the digital model of the patient’s lower jaw portion are based on one or more intraoral scans ([0097] reciting “As described above, the first machine learning model can be implemented in a digital orthodontic treatment planning software. In one implementation, the first crop comprises a low resolution crop and pertains to an area of the original 3D scan that includes the upper and/or lower bones of the patient's jaw. This operation can therefore be used to generate segmentation data of the upper/lower bones of the patient's jaw.”; [0091] reciting “At an operation 202, the system may automatically receive three-dimensional (3D) scan of a patient's dentition. The scan may be generated from 3D scanning machine collected directly from the patient (e.g., using an intraoral scanner, a CT scanner, a CBCT scanner, a MRI scanner)”), ;
generating a two-dimensional (2D) alignment image based on projecting the 3D alignment model ([0072] reciting “The results may include 3D virtual representations of the dental arch, 2D images or renditions of the dental arch, etc.”; [0073] reciting “The 3D segmentation system can be configured to input one or more different areas of the 2D scan, 3D scan, or 3D model into a machine learning model to automatically segment the scan or model into individual dental components, including segmenting the scan or model into individual teeth, bones, interproximal spaces between teeth, and/or gingiva.”);
and outputting the 3D alignment model ([0016] reciting “…automatically segmenting the 3D scan with one or more convolutional neural networks; incorporating the segmented 3D scan into a 3D dental model of a virtual treatment plan; and outputting the virtual treatment plan.”)
92 Chernov does not explicitly teach … wherein the 3D alignment model includes a TMJ parameter; determining a location of a virtual camera and a location of a projection plane associated with the virtual camera in 3D space with respect to a position of the 3D alignment model, wherein the location of the virtual camera establishes a 3D relationship between the 3D alignment model and the projection plane; generating a two-dimensional (2D) alignment projection image based on projecting the 3D alignment model onto the projection plane; determining a difference estimate between a 2D dental image of the patient’s teeth and the 2D alignment projection; iteratively adjusting the TMJ parameter based on the difference estimate and repeating the steps of generating the 2D alignment projection image and determining the difference estimate until the difference is less than a threshold or until the number of iterations exceeds a second threshold; and outputting the 3D alignment model including the TMJ parameter.
93 Karanam teaches determining a location of a virtual camera and a location of a projection plane associated with the virtual camera in 3D space with respect to a position of the 3D alignment model, wherein the location of the virtual camera establishes a 3D relationship between the 3D alignment model and the projection plane ([0022] reciting “based on the 3D human model, whether the position and/or pose of the patient 106 meets the requirements of a predetermined protocol (e.g., while the patient 106 is standing in front of the medical scanner 102 or lying on a scan bed), and provide real-time confirmation or adjustment instructions (e.g., via the display device 112), to help the patient 106 get into the desired position and/or pose.”; [0031] reciting “Using the mapping relationship, a plurality of 3D key body locations may be determined based on the vertices of the 3D model 302 and the 3D key body locations may be projected into a 2D image frame (e.g., using predetermined camera and/or projection parameters) to obtain the set of key point locations. Similarly, given the vertices of the 3D human model 302, a shape outline of the person may also be obtained, for example, using the predetermined camera and/or projection parameters.”); generating a two-dimensional (2D) alignment projection image based on projecting the 3D alignment model onto the projection plane ([0022] reciting “For instance, the processing device 108 may align scan images of the patient 106 from the repository 114 with the 3D human model to allow the scan images to be presented (e.g., via display device 112) and analyzed with reference to the anatomical characteristics (e.g., body shape and/or pose) of the patient 106 as indicated by the 3D human model.”; [0031] reciting “Using the mapping relationship, a plurality of 3D key body locations may be determined based on the vertices of the 3D model 302 and the 3D key body locations may be projected into a 2D image frame (e.g., using predetermined camera and/or projection parameters) to obtain the set of key point locations. Similarly, given the vertices of the 3D human model 302, a shape outline of the person may also be obtained, for example, using the predetermined camera and/or projection parameters.”);
94 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov) to incorporate the teachings of Karanam to provide a method to include a location of a type of virtual camera and a projection plane (a 2d area) for the 3d space in the 3d alignment model including their relationships and types of projections, utilizing the models provided by Chernov. Doing so would allow the images to be analyzed with reference to the anatomical characteristics as stated by Karanam ([0022] recited).
95 Chernov in view of Karanam does not explicitly teach … wherein the 3D alignment model includes a TMJ parameter; determining a difference estimate between a 2D dental image of the patient’s teeth and the 2D alignment projection; iteratively adjusting the TMJ parameter based on the difference estimate and repeating the steps of generating the 2D alignment projection image and determining the difference estimate until the difference is less than a threshold or until the number of iterations exceeds a second threshold; and outputting the 3D alignment model including the TMJ parameter.
96 Liu teaches determining a difference estimate between a 2D dental image of the patient’s teeth and the 2D alignment projection ([0042] reciting “In this embodiment, one (or preferably more) 2D images of the current dental arch or a portion of the current dental arch (e.g., picture of ill-fitting region) are provided (see 300 in FIG. 3) and can be used to correct the position of the subject's teeth. For example, the dentist or practitioner may provide images (including x-rays, photographs, etc.) of the subject's teeth. The digital model of the subject's teeth (the model to be corrected, 301) may then be compared to these images (302), and the difference between the actual tooth position shown in the images (or scans) and the digital model may be calculated.”);
iteratively adjusting the TMJ parameter based on the difference estimate and repeating the steps of generating the 2D alignment projection image and determining the difference estimate until the difference is less than a threshold or until the number of iterations exceeds a second threshold ([0043] reciting “Using the digital model, the teeth position are iteratively examined (e.g., through each projection of the teeth), and edge matching can be used to subtract the difference between individual tooth in the actual position of the dental arch with the corresponding teeth positioned in the 2D image projection from the model.”; [0045] reciting “Also as described above for the 3D scanning technique, the accuracy of the position of the corrected dental arch tooth models may be checked (304). For example, surface area subtraction may be done to determine if the difference between the corrected model and the image(s) provided falls within an acceptable range. Thus, 2D projections from the digital dental arch model may be generated in the same perspective as the provided image(s), and the edges of the surfaces compared. Differences in the two surfaces (e.g., where they do not align) may be determined, and compared to a threshold value. As mentioned above, a threshold error may be set (e.g., less than 5%, less than 1%,less than 0.5%, less than 0.1%, less than 0.05%, less than 0.01%, or some intermediate value), and an error exceeding this threshold results in a "failure" of the correction technique.”);
97 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam) to incorporate the teachings of Liu to provide methods that determine a type of difference between a dental image and the alignment model, as well as to import the dental information when the difference is less than a threshold utilizing the various dental images and alignment models provided by the teachings of Chernov in view of Karanam. Doing so would allow the ability to make new tooth models as stated by Liu ([0045] recited).
98 Chernov in view of Karanam and Liu does not explicitly teach … wherein the 3D alignment model includes a TMJ parameter; …iteratively adjusting the TMJ parameter based on the difference estimate …; and outputting the 3D alignment model including the TMJ parameter.
99 Malfliet teaches … wherein the 3D alignment model includes a TMJ parameter …iteratively adjusting the TMJ parameter based on the difference estimate …; and. outputting the 3D alignment model including the TMJ parameter ([0039] reciting “The absolute positioning is meant to transfer the relation between the condyles and the maxilla from the patient to the articulator so that the model of the upper dentition is located in the same three-dimensional position with respect to the condylar replications on the articulator.”; [0047] reciting “Another way of using a virtual articulator to determine the impact of a proposed dental modification on the temporomandibular joint(s) is by simulating the movement of the jaws when closing the mouth. Due to the occurring tooth contacts, the original rotational character gets an additional translational component causing a posterior displacement of the condyles. The closing movement is simulated on a virtual articulator both for the unmodified and the modified model. The amount of posterior displacement is compared in both situations and the relative difference is computed.”; [0050] reciting “Moreover, a virtual articulator allows to quantitatively compare a number of simulations easily because the simulated movements are reproducible, repeatable, durable and stable.”; [0055] reciting “For example, computer may further include random-access memory ("RAM"), read-only memory ("ROM"), as well as a display adapter for connecting system bus to a video display terminal, and an optional input/output (I/O) adapter for connecting peripheral devices (e.g., disk and tape drives) to system bus. The video display terminal can be the visual output of computer, which can be any suitable display device such as a CRT-based video display well-known in the art of computer hardware.”).
100 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Chernov in view of Karanam and Liu) to incorporate the teachings of Malfliet to provide a method that can provide a specific TMJ that can be modified utilizing the 3d alignment methods that are taught by the teachings of Chernov in view of Karanam and Liu. Doing so would allow dental modifications like the replacement of one or more teeth by artificial teeth, the replacement of one or more parts of a tooth by a prosthetic reconstruction such as a dental crown or veneer, the rearrangement of one or more existing teeth (orthodontic treatment), the distraction of one or both jaws in order to reposition the teeth (orthognatic treatment) and/or modifications of the occlusal surfaces of the teeth as stated by Malfliet ([Abstract] recited).
Conclusion
101 Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
102 Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNY TRAN LE whose telephone number is (571)272-5680. The examiner can normally be reached Mon-Thu: 7:30am-5pm; First Fridays Off; Second Fridays: 7:30am-4pm.
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/JOHNNY T LE/ Examiner, Art Unit 2614
/KENT W CHANG/ Supervisory Patent Examiner, Art Unit 2614
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