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 .
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. The following title is suggested: Three-.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: characters 1, 4, 5 , 6 and 7 of figure4. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) 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. 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.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 17 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. It is unclear what the limitation “based on a center of gravity of a dental arch including the tooth” is being applied to. The claim could be interpreted as the identification of parts, the division of parts, or the plurality of planes being based on a center of gravity of a dental arch including the tooth or some combination of the above. Examiner has sought clarity in the drawings and specification with little success. The specification describes the utilization of the dental arches center of gravity for identification on page 38. Page 38 states “the buccal surface, a surface further from the center of gravity of the dental arch” and “the lingual surface, a surface closer to the center of gravity of the dental arch”. This description of the use of the center of gravity gives some clarity, however it is still unclear to what the “further from” and “closer to” are referring to, for the purpose of examination, examiner is interpreting these as being compared to one another. However, on page 38, the specification states “based on a plurality of parts in which the tooth is divided along a plurality of planes along the tooth axis passing through the center of gravity of the tooth, as well as the center of gravity of the dental arch including the tooth, data processing apparatus 10 can identify each of these plurality of parts”. This passage recites a similar limitation as the claim which may be interpreted as the tooth’s division being based on both the plurality of planes “as well as the center of gravity of the dental arch”. Because a division of the tooth and identification of a tooth are intertwined, Examiner will be interpreting the claim as both division and identification being based upon the center of gravity. For example, a tooth is divided based on distance to the center of gravity of the dental arch, and this division based on distance to the center of gravity of the dental arch is used for identification, i.e. the buccal side is the furthest of the divided portions from the center of gravity of the dental arch. 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.
Claim 1-11, 19-23, 26 is/are rejected under 35 U.S.C. 103 as being obvious over Hashimoto (US 2022/0058372 A11) in view of Azernikov (US 2018/0028294 A1).
Regarding claim 1, Hashimoto teaches A data processing apparatus (fig. 1 #100 – identification device, paragraphs [0006], [0029]-[0040]) for processing three-dimensional data (paragraph [0006] – receives three-dimensional data), the data processing apparatus comprising:
input processing circuitry (fig. 5 #1102, paragraphs [0006], [0078] – “Computing device 530 may also be referred to as processing circuitry.”, [0081]-[0082] – “identification device 100 includes an input unit 1102, a profile acquisition unit 1119, […]. Each of these functions is implemented by computing device”) configured to acquire the three-dimensional data (paragraph [0082] – “Input unit 1102 receives three-dimensional data acquired by three-dimensional scanner 200.") including three-dimensional position information corresponding to each of a plurality of points representing a surface shape of intraoral objects including a tooth (paragraph [0006] – “three-dimensional data including data of the tooth”, paragraph [0031] – “Specifically, three-dimensional scanner 200 scans the inside of an oral cavity to acquire, as three-dimensional data, position information ( coordinates of each of axes in the vertical direction, the horizontal direction, and the height direction) at each of a plurality of points forming a tooth to be scanned, for which an optical sensor or the like is used”);
computing processing circuitry (figure 1, reference 100, i.e. a computer, paragraph [0078]) configured to perform a process of identifying a type of the tooth, based on the three-dimensional data acquired by the input processing circuitry (paragraphs [0006]-[0008], [0033], identifies a type of the tooth based on the three-dimensional data acquired by the scanner); and
output processing circuitry configured to output a result of the process performed by the computing processing circuitry (paragraphs [0006], [0039], [0040], display shows the identification result).
Hashimoto fails to explicitly teach a process of identifying each of a plurality of parts of the tooth.
However, Azernikov teaches a process of identifying each of a plurality of parts of the tooth (paragraphs [0017] – “The probability vector can include a probability of each dental feature being present in the at least a portion of the dentition”, [0019], [0020] – “A dental feature can be an aspect or a feature of tooth surface anatomy that includes, but not limited to, buccal and lingual cusps, distobuccal and mesiobuccal inclines, distal and mesial cusp ridges, distolingual and mesiolingual inclines, an occlusal surface, and buccal and lingual arcs” In other words a dental feature which is identified is analogous to a part of the tooth). Azernikov is considered analogous to the claimed invention as it is in the same field of 3D dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Azernikov with Hashimoto and substitute Hashimoto’s type identification with Azernikov’s part identification because such a modification is the result of simple substitution of one known element for another producing a predictable result. More specifically, Hashimoto’s type identification and Azernikov’s part identification perform the same general and predictable function, the predictable function being dental identification. Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself - that is in the substitution of Hashimoto’s type identification by replacing it with Azernikov’s part identification. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 2, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein in a case where the tooth is a first molar, a second molar, a third molar, a first premolar, or a second premolar of upper jaw, the plurality of parts include at least one of an occlusal surface, a distal surface, a mesial surface, a palatal surface, and a buccal surface of the tooth (paragraph [0085] – “When the teeth to be scanned by three-dimensional scanner 200 are a canine and a molar in the upper jaw, user 1 scans the inside of the oral cavity of subject 2 such that the three-dimensional image to be obtained includes at least: an image of an area on the buccal side; an image of an area on the palate side; and an image of an occlusion area.)
in a case where the tooth is a canine, a lateral incisor, or a central incisor of the upper jaw, the plurality of parts include at least one of a distal surface, a mesial surface, a palatal surface, and a labial surface of the tooth (paragraph [0085] – “when the tooth to be scanned by three-dimensional scanner 200 is an incisor in an upper jaw, user 1 scans the inside of the oral cavity of subject 2 such that the three-dimensional image to be obtained includes at least: an image of an area on the upper lip side [labial surface]; an image of an area on the palate side; and an image of an area on the incisal edge side”),
in a case where the tooth is a first molar, a second molar, a third molar, a first premolar, or a second premolar of lower jaw, the plurality of parts include at least one of an occlusal surface, a distal surface, a mesial surface, a lingual surface, and a buccal surface of the tooth, (paragraph [0085] – “When the teeth to be scanned by three-dimensional scanner 200 are a canine and a molar in the lower jaw, user 1 scans the inside of the oral cavity of subject 2 such that the three-dimensional image to be obtained includes at least: an image of an area on the buccal side; an image of an area on the tongue side [lingual surface]; and an image of an occlusion area.”) and
in a case where the tooth is a canine, a lateral incisor, or a central incisor of the lower jaw, the plurality of parts include at least one of a distal surface, a mesial surface, a lingual surface, and a labial surface of the tooth. (paragraph [0085] – “When the tooth to be scanned by three-dimensional scanner 200 is an incisor in the lower jaw, user 1 scans the inside of the oral cavity of subject 2 such that the three-dimensional image to be obtained includes at least: an image of an area on the lower lip side [labial surface]; an image of an area on the tongue side [lingual surface]; and an image of an area on the incisal edge side”)
Regarding claim 3, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Azernikov further teaches wherein in a case where the tooth is a first molar, a second molar, a third molar, a first premolar, or a second premolar, the plurality of parts include respective cusps constituting the tooth (figs. 8 & 9, paragraphs [0020], [0035], [0118]). While Azernikov does not specify the plurality of cusps is included in the plurality of parts in the case of a molar or premolar, it can be assumed so because the methods of Azernikov are applied to any tooth, which includes the claim’s described molars and premolars. Additionally figures 8 and 9, which are described as showing detected cusps, also comprise depictions of molars and premolars, meaning the respective cusps are detected in a case where the tooth is a molar or premolar. The motivation to combine Azernikov and Hashimoto with respect to claim 3 would have been the same as that of claim 1.
Regarding claim 4, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein in a case where the tooth is a canine, a lateral incisor, or a central incisor, the plurality of parts include a plurality of surfaces constituting a labial surface of the tooth (paragraph [0085] – When the tooth to be scanned is an incisor the three-dimensional image includes an area on the upper/lower lip side. This area on the upper/lower lip side is a plurality of surfaces which constitute a labial surface).
Regarding claim 5, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein the computing processing circuitry is further configured to identify a tooth to which each of the plurality of parts belong, among teeth of upper jaw and lower jaw (paragraphs [0033]-[0035], [0086] –the plurality of parts is comprised in the three-dimensional data which is used in identifying a tooth).
Regarding claim 6, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein the computing processing circuitry is further configured to identify a type of the tooth, based on the three-dimensional data acquired by the input processing circuitry (paragraph [0033]), and a first estimation model having undergone machine learning (paragraphs [0036]-[0037]).
Regarding claim 7, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 6. Hashimoto further teaches wherein the first estimation model includes a first neural network having undergone machine learning to identify the type of the tooth based on the three-dimensional data input to the first neural network (figs. 5-6, paragraphs [0006], [0036]).
Regarding claim 8, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Azernikov further teaches wherein the computing processing circuitry is further configured to identify each of the plurality of parts, based on the three-dimensional data acquired by the input processing circuitry (paragraphs [0017] – “The probability vector can include a probability of each dental feature being present in the at least a portion of the dentition”, [0019], [0020] – “A dental feature can be an aspect or a feature of tooth surface anatomy that includes, but not limited to, buccal and lingual cusps, distobucall and mesiobuccal inclines, distal and mesial cusp ridges, distolingual and mesiolingual inclines, an occlusal surface, and buccal and lingual arcs”, paragraph [0096] – “the deep neural networks used in the present disclosure may have the scan data (such as the dental models) or preprocessed scan data (such as the depth maps or spherical distance maps) as input”), and a second estimation model having undergone machine learning (paragraphs [0008], [0018], [0019]). The motivation to combine the estimation model which identifies each of the plurality of parts of Azernikov with the tooth type identification (which involves an estimation model) of Hashimoto would have been the same substitution motivation as that of claim 1.
Regarding claim 9, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 8. Azernikov further teaches wherein the second estimation model includes a second neural network having undergone machine learning to identify each of the plurality of parts, based on the three-dimensional data input to the second neural network (paragraphs [0008], [0019]-[0021]). The motivation to combine Azernikov and Hashimoto with respect to claim 9 would have been the same as that of claims 1 and 8.
Regarding claim 10, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Azernikov further teaches wherein the computing processing circuitry is further configured to identify an artificially-formed part of the tooth based on the three-dimensional data acquired by the input processing circuitry, and a third estimation model having undergone machine learning (paragraphs [0012], [0013]-“ The category of dentition or dental feature can include a lower jaw, an upper jaw, a prepared jaw, an opposing jaw, a set of tooth numbers, and dental restoration types. The restoration types can include crowns, inlays, bridges, and implants.”, [0020], [0066]- “Training data sets can be specifically designed to train one or more deep neural networks of training module 123 to identify certain dentition features, surface tooth anatomy, dental restorations, etc.). The dental restorations which can be identified by a deep neural network are analogous to artificially-formed parts of a tooth. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Azernikov with Hashimoto and substitute Hashimoto’s type identification with Azernikov’s dental restoration identification because such a modification is the result of simple substitution of one known element for another producing a predictable result. More specifically, Hashimoto’s type identification and Azernikov’s dental restoration identification perform the same general and predictable function, the predictable function being dental identification. Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself - that is in the substitution of Hashimoto’s type identification by replacing it with Azernikov’s dental restoration identification. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 11, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 10. Azernikov further teaches wherein the third estimation model includes a third neural network having undergone machine learning to identify the artificially-formed part (paragraph [0066]-[0067]), based on the three-dimensional data input to the third neural network (paragraph [0007]). The motivation to combine Azernikov and Hashimoto with respect to claim 11 would have been the same as that of claim 10.
Regarding claim 19, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein the output processing circuitry is further configured to output image data for displaying a diagram or a table indicating a result of the process (paragraphs [0039], [0040], fig. 1 display #300 shows a diagram displayed as output image data).
Regarding claim 20, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 19. Hashimoto further teaches wherein the image data includes data for displaying the tooth, together with a result of the process, in at least one of two dimensions and three dimensions (paragraphs [0039], [0040], [0155], fig. 1 display #300 shows a diagram displayed as output image data, an image is a two-dimensional output).
Regarding claim 21, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein a result of the process includes information on a color associated with each of the plurality of parts (figs. 6, 8-9, paragraphs [0038], [0095], [0099], [0115], [0116]).
Regarding claim 22, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein
the computing processing circuitry is further configured to determine at least one of: whether a part of the tooth having been colored has a defect and a degree of defect of the part, based on the three-dimensional data acquired by the input processing circuitry (paragraphs [0114]-[0116] error between identification result and correct data can be considered a degree of defect of the part, Hashimoto additionally compares the estimated color information of a specific tooth with correct color information which is used to update the identification device’s estimation model to properly identify the color information associated with the tooth), and
the computing processing circuitry is further configured to associate, based on the result of the process, the part of the tooth having been colored, with a result of determining whether the part of the tooth having been colored has the defect (paragraph [0116] Hashimoto associates the estimated color information with a type and number of tooth, comparing this estimated information with the ground truth information and updating the estimation model depending on whether this is correct or incorrect (has a defect)).
Regarding claim 23, Hashimoto in view of Azernikov teaches The data processing apparatus according to claim 1. Hashimoto further teaches wherein
the computing processing circuitry is further configured to determine an actual color of each of the plurality of parts, (paragraphs [0038] – “the "tooth information" may include information of colors assigned to the respective teeth or information of symbols assigned to the respective teeth”, paragraphs [0093]-[0095], [0099]) based on the three-dimensional data acquired by the input processing circuitry (paragraphs [0084] – “the three-dimensional data input into input unit 1102 includes three-dimensional position information at each of points of a tooth and color information at each of points of a tooth”, [0093], [0099] – “predetermined color information (RGB values) is associated with each of points of a tooth corresponding to the three-dimensional data”), and
the computing processing circuitry is further configured to associate, based on the result of the process, each of the plurality of parts, with a result of the determination of the actual color of each of the plurality of parts (paragraphs [0095], [0096], [0126], [0127] ).
Regarding claim 26, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein the three- dimensional data includes at least one of three-dimensional scanner data acquired by scanning the tooth using a three-dimensional scanner (paragraph [0007])
Claim(s) 12 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Azernikov as applied to claim 1 above, and further in view of Kaji (JP 7324735 B2).
Regarding claim 12, Hashimoto in view of Azernikov teach the data processing apparatus according to claim 1.
Hashimoto in view of Azernikov fail to teach wherein the computing processing circuitry is further configured to identify a lesion of the tooth or gum, based on the three-dimensional data acquired by the input processing circuitry, and a fourth estimation model having undergone machine learning.
However, Kaji teaches wherein the computing processing circuitry is further configured to identify a lesion of the tooth or gum, based on the three-dimensional data acquired by the input processing circuitry, and a fourth estimation model having undergone machine learning (paragraphs 2 of page 2 – “the first embodiment uses AI (Artificial Intelligence) possessed by the identification device 100 to automatically identify the lesion site based on the three-dimensional data 122 acquired by the three-dimensional scanner”, paragraph 4 of page 2 – “The identification device 100 performs identification processing for identifying what kind of part the part corresponding to the input three-dimensional data 122 is, based on the input three-dimensional data 122 and an estimation model including a neural network”). Kaji is considered analogous to the claimed invention as it is in the same field of 3D dental imaging and machine learning. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Hashimoto in view of Azernikov’s computer processing circuitry to include Kaji’s lesion identification because such a modification is the result of applying a known technique to a known device ready for improvement to yield predictable results. More specifically, Kaji’s lesion identification permits early disease detection. This known benefit is applicable to Hashimoto in view of Azernikov’s computing processing circuitry as they both share characteristics and capabilities, namely, they are directed to dental imaging. Therefore, it would have been recognized that modifying Hashimoto in view of Azernikov to include Kaji’s lesion identification would have yielded predictable results because (i) the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate lesion identification in dental imaging and (ii) the benefits of such a combination would have been recognized by those of ordinary skill in the art.
Regarding claim 13, Hashimoto in view of Azernikov and in further view of Kaji teach the data processing apparatus according to claim 12. Kaji further teaches wherein the fourth estimation model includes a fourth neural network having undergone machine learning to identify the lesion, based on the three-dimensional data input to the fourth neural network (paragraphs 2-5 of page 2 – “An "estimated model" includes a neural network and parameters used by the neural network” from paragraph 4). The motivation to combine Kaji with Hashimoto in view of Azernikov with respect to claim 13 would have been the same as that of claim 12.
Claim(s) 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Azernikov as applied to claim 1 above, and further in view of Yoshikawa (US 2024/0252105 A1).
The applied reference, Yoshikawa, has a common applicant with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2).
This rejection under 35 U.S.C. 103 might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C.102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B); or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement. See generally MPEP § 717.02.
Regarding claim 14, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1.
Hashimoto in view of Azernikov fails to teach wherein the computing processing circuitry is further configured to estimate a depth of a periodontal pocket in the tooth, based on the three-dimensional data acquired by the input processing circuitry, and a fifth estimation model having undergone machine learning.
However, Yoshikawa teaches wherein the computing processing circuitry is further configured to estimate a depth of a periodontal pocket in the tooth (paragraphs [0065], [0103]-[0106]), based on the three-dimensional data acquired by the input processing circuitry (paragraph [0042]), and a fifth estimation model having undergone machine learning (paragraph [0057]). Yoshikawa is considered analogous to the claimed invention as it is in the same field of dental imaging and machine learning. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Hashimoto in view of Azernikov’s computer processing circuitry to include Yoshikawa’s periodontal pocket depth estimation because such a modification is the result of applying a known technique to a known device ready for improvement to yield predictable results. More specifically, Yoshikawa’s periodontal pocket depth estimation permits early disease detection. This known benefit is applicable to Hashimoto in view of Azernikov’s computing processing circuitry as they both share characteristics and capabilities, namely, they are directed to dental imaging. Therefore, it would have been recognized that modifying Hashimoto in view of Azernikov to include Yoshikawa’s periodontal pocket depth estimation would have yielded predictable results because (i) the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate lesion identification in dental imaging and (ii) the benefits of such a combination would have been recognized by those of ordinary skill in the art.
Regarding claim 15, Hashimoto in view of Azernikov and in further view of Yoshikawa teach the data processing apparatus according to claim 14. Yoshikawa further teaches wherein the fifth estimation model includes a fifth neural network having undergone machine learning to estimate the depth of the periodontal pocket (paragraphs [0056], [0057]), based on the three-dimensional data input to the fifth neural network (paragraphs [0057], [0065]). The motivation to combine Yoshikawa and Hashimoto in view of Azernikov with respect to claim 15 would have been the same as that of claim 14.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Azernikov as applied to claim 1 above, and further in view of Saphier (US 2021/0353152 A1).
Regarding claim 16, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1.
Hashimoto in view of Azernikov fails to teach wherein the computing processing circuitry is further configured to estimate a premature contact position where upper and lower dental arches make premature contact when the upper and lower dental arches are occluded, based on the three-dimensional data acquired by the input processing circuitry.
However, Saphier teaches wherein the computing processing circuitry is further configured to estimate a premature contact position where upper and lower dental arches make premature contact when the upper and lower dental arches are occluded, based on the three-dimensional data acquired by the input processing circuitry (paragraphs [0096]-[0098], [0405] – “analyzing occlusal contacts between the upper dental arch and the lower dental arch”, [0458] – “Using this occlusal map, analysis of the occlusion and interference existing in the maxillomandibular complex can be carried out”). Saphier is considered analogous to the claimed invention as it is in the same field of three-dimensional dental imaging and analysis. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Saphier with Hashimoto in view of Azernikov in order to improve the qualitative evaluations of Azernikov by incorporating the premature contact estimation of Saphier, and improving the evaluation of restoration fit relative to occlusal contact with teeth of opposing jaws as is discussed in paragraph [0023] of Azernikov.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Azernikov as applied to claim 1 above, and further in view of Sakamoto (US 2021/0196213 A1) and Manai (US 2012/0072177 Al).
Regarding claim 17, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein the computing processing circuitry is further configured to divide the tooth by a plurality of planes along a tooth axis and based on a dental arch including the tooth (fig. 7, paragraph [0085])
Azernikov further teaches wherein the computing processing circuitry is further configured to identify each of the plurality of parts, based on the plurality of parts into which the tooth is divided (paragraphs [0014]-[0016] [0090]-[0094])
Hashimoto in view of Azernikov fails to teach a plurality of planes passing through a center of gravity of the tooth, and based on a center of gravity of a dental arch.
However, Sakamoto teaches a plurality of planes along a tooth axis passing through a center of gravity of the tooth (fig. 8, 11-13, paragraphs [0080], [0083], [0104],[0105], [0116]). Sakamoto describes a method of a tooth axis in a global coordinate system, rather than a local one, to compare characteristics of different teeth. In this process Sakamoto projects the position of a tooth, represented as a center of gravity, onto the planes of the global coordinate system. This is used to calculate the tooth axis, which is further used to estimate the curve of the dental arch. This information is then outputted to the display and aids in recognizing a relative relationship between teeth. Sakamoto is considered analogous to the claimed invention as it is in the same field of dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Sakamoto with Hashimoto in view of Azernikov in order to improve recognizing relative relationship between teeth, which may in turn improve recognition of a tooth type or tooth part present in Hashimoto in view of Azernikov.
Hashimoto in view of Azernikov and Sakamoto fail to teach based on a center of gravity of a dental arch.
However, Manai teaches divide and identify parts based on a center of gravity of a dental arch (paragraphs [0031], [0032], [0039]). Manai describes an occlusion estimation system for prosthesis design. This process involves generating 3D models of a patients lower and upper teeth. This process determines “contact points” which “may define the placement of one of the 3D models with respect to another 3D model”, in other words the contact points define the occlusion between the two jaws (dental arches). This process of determining contact points and occlusion (which can be considered analogous to parts under BRI and claim 17s lack of dependency on claim 2’s recitation of specific parts) uses an iterative process with a stop condition utilizing the contact points’ relationship to a center of gravity of the respective dental arch. Additionally, Manai describes segmentation of the 3D model based on the center of gravity “determining whether two contact points are on the opposite sides of the center of gravity may include defining a bisector or bisection plane through the center of gravity that splits the first 3D model into two segments, for example, a left segment and a right segment, and, optionally, splits the second 3D model into two segments, for example, the left segment and the right segment.” (paragraph [0039]). Manai is considered analogous to the claimed invention as it is in the same field of 3D dental imaging. Therefore, at the time the invention was made, it would have been obvious to one of ordinary skill in the art to modify the part identification of Hashimoto in view of Azernikov and Sakamaoto to include Manai’s occlusion estimation based on a center of gravity of a dental arch because such a modification is based on the use of known techniques to improve similar devices in the same way. More specifically, Manai’s occlusion estimation based on a center of gravity is comparable to the part identification of Hashimoto in view of Azernikov and Sakamaoto, which includes the use of a tooth’s center of gravity. Therefore, it is within the capabilities of one of ordinary skill in the art to modify Hashimoto in view of Azernikov’s part identification to include center of gravity based occlusion estimation with the predictable result of identifying a tooth part such as an occlusal surface because an occlusion estimation process is taught by Manai.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Azernikov, Sakamoto and Manai as applied to claim 17 above, and further in view of Cofar (US 2023/0048898 A1).
Regarding claim 18, Hashimoto in view of Azernikov, Sakamoto, and Manai teaches the data processing apparatus according to claim 17. Azernikov further teaches wherein the computing processing circuitry is further configured to identify an occlusal surface of the tooth (paragraphs [0019], [0020])
Hashimoto in view of Azernikov, Sakamoto and Manai fails to teach using at least one of a cylinder, an elliptical column, and a prism of which central axes are each the tooth axis.
However, Cofar teaches identifying a tooth using at least one of a cylinder, an elliptical column, and a prism of which central axes are each the tooth axis. (paragraphs [0031], [0044], [0099] [0197], [0383], [0394], [0397] – bounding box is a rectangular prism, beam shaped bounding box can be considered a cylinder or elliptical column). Cofar describes utilizing a bounding box which bounds a tooth, to identify information about the tooth such as the type of the tooth. Cofar also states “the present invention could be extended to characterize the 3D shape of teeth, including the position and size and shape of protrusions and cavities in the premolars or molars” (paragraph [0233]). The 3D shape of premolars and molars, including position, size and shape of protrusions and cavities, is essentially a broader definition of the occlusal surface. Cofar is considered analogous to the claimed invention as it is in the same field of three-dimensional dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Cofar with Hashimoto in view of Azernikov, Sakamoto and Manai to integrate the system with occlusal surface determination, as suggested by Cofar, in order to improve the segmentation, identification and real world applicability of the dental model.
Claim(s) 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Azernikov as applied to claim 1 above, and further in view of Chang, Yu-Bing & Gateno, Jaime & Xiong, Zixiang & Zhou, Xiaobo & Wong, Stephen. (2010). An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion. IEEE Transactions on Medical Imaging. 29. 1652-1663. 10.1109/TMI.2010.2049526. (hereinafter "Chang").
Regarding claim 24, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches respective positions of a second molar of a left side of a lower jaw, a second molar of a right side of a lower jaw, a left central incisor and a right central incisor of lower jaw (figs 7-8, fig. 9 #118 shows a second premolar of the left side of lower jaw, #116 shows position information, paragraphs [0034], [0038], [0084], [0099]), and
the output processing circuitry is further configured to output image data for displaying an occlusal area generated based on the second molar of the left side of lower jaw, the second molar of the right side of lower jaw, and the left central incisor and the right central incisor of lower jaw (fig. 1, 6-9 paragraph [0153]).
Hashimoto in view of Azernikov fails to explicitly teach the result of the process includes respective positions of a distal buccal cusp of a second molar of a left side of lower jaw , a distal buccal cusp of a second molar of a right side of lower jaw, and mesial surfaces of a left central incisor and a right central incisor of lower jaw, and
the output processing circuitry is further configured to output image data for displaying an occlusal plane generated based on the distal buccal cusp of the second molar of the left side of lower jaw, the distal buccal cusp of the second molar of the right side of lower jaw, and a midpoint of the mesial surfaces of the left central incisor and the right central incisor of lower jaw.
However, Chang teaches wherein
the result of the process includes respective positions of a distal buccal cusp of a molar of a left side of lower jaw, a distal buccal cusp of a molar of a right side of lower jaw (figs. 3-5, Section III A subsection 1) Feature Points in the Mandibular Model – “The feature points on the posterior teeth are the peaks on the buccal cusps” ), and mesial surfaces of a left central incisor and a right central incisor of lower jaw (Section V paragraph 2 – “They are the mesiobuccal15 cusp of the first right molar , the mesiobuccal cusp of the first left molar , and the central dental midline . The coordinates of these landmarks are used later to compare with the same landmarks in the experimental group.”; the central dental midline, is the contact point between the mesial surfaces of the central incisors, the coordinates of this point is the same as the that of the central dental midline in an ideal occlusion, such as that which would be present in the gold standard dataset described in section II), and
the output processing circuitry is further configured to output image data for displaying an occlusal plane generated based on the distal buccal cusp of the molar of the left side of lower jaw, the distal buccal cusp of the molar of the right side of lower jaw (Section III A – “The occlusal plane ( x-O-y plane) of the dental model is determined by identifying distobuccal 11 cusps of the first molar and the incisal edge of a central incisor 12”), and a midpoint of the mesial surfaces of the left central incisor and the right central incisor of lower jaw (fig. 9 – the “mandibular central dental midline (Point C)” is analogous to a midpoint of the left central incisor and the right central incisor of the lower jaw). Chang describes a method of reestablishing digital dental occlusion which involves identifying the distobuccal cusps of molars, and the central dental midline to generate a representative occlusal plane. These landmarks are “commonly used in clinical practice” as representative of an occlusal surface as three points are necessary to derive an occlusal plane. While Chang does not specify the use of a “second” molar, Hashimoto does, and it would have been obvious to one of ordinary skill in the art to utilize the position determination of Chang with the specific teeth of Hashimoto for the following reasons. Chang is considered analogous to the claimed invention as it is in the same field of dental imaging and modeling. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Chang with Hashimoto in view of Azernikov to implement a complete display of the dental model (occlusal plane) rather than the partial display in Hashimoto (occlusion area) as such a modification would have been obvious to try and one of ordinary skill in the art could have pursued the known potential solutions with a reasonable expectation of success.
Claim(s) 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Azernikov as applied to claim 1 above, and further in view of Paley (US 7,912,257 B2).
Regarding claim 25, Hashimoto in view of Azernikov teaches the data processing apparatus according to claim 1. Hashimoto further teaches wherein
the three-dimensional data is three-dimensional scanner data acquired through scanning of the tooth using a three-dimensional scanner (paragraph [0007] – “The scanner system includes: a three-dimensional scanner that acquires three-dimensional data including data of the tooth”), and
Hashimoto in view of Azernikov fails to teach the output processing circuitry is further configured to output, in real time, the result of the process acquired during scanning with the three-dimensional scanner.
However, Paley teaches the output processing circuitry is further configured to output, in real time, the result of the process acquired during scanning with the three-dimensional scanner (title, abstract, col. 8 lines 56-64). Paley is considered analogous to the claimed invention as it is in the same field of three-dimensional dental imaging. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Paley with Hashimoto in view of Azernikov to improve the quality and speed of data acquisition.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sagawa (US 2025/0118433 A1) describes a system of AI dental diagnosis using OCT imaging which includes OCT data acquired by imaging the tooth using an optical coherence tomography device (paragraphs [0008], [0041]).
Shim (US 2022/0398738 A1) describes a method of automated tooth segmentation utilizing three-dimensional scan data and a convolutional neural network.
Kaufmann (US 7,004,754 B2) describes a crown and gingiva detection system which describes orienting a three dimensional model about the center of gravity of a dental arch.
Terada, Kazuto & Kameda, Takashi & Kageyama, Ikuo & Sakamoto, Makoto. (2019). Estimation of three-dimensional long axes of the maxillary and mandibular first molars with regression analysis. Anatomical Science International. 95. 126-133. 10.1007/s12565-019-00506-1. Terada describes a linear regression system for determining a tooth axis through the tooth’s center of gravity.
Gillot M, Miranda F, Baquero B, et al. Automatic landmark identification in cone-beam computed tomography. Orthod Craniofac Res. 2023; 26: 560-567. doi:10.1111/ocr.12642 describes a system of automatic landmark identification using CBCT data. These landmarks are very similar to the described tooth parts described in the claimed invention. Some example landmarks which are identified are the mesial buccal cusp of the mandibular right permanent first molars, and the incisal edge of the mandibular right permanent central incisor, etc.. More of the identified landmarks can be seen in Table 1.
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/AIDAN W MCCOY/Examiner, Art Unit 2611
/HAIXIA DU/Primary Examiner, Art Unit 2611
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