Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite receiving scan data and generating data. This judicial exception is not integrated into a practical application because the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because storing and retrieving information in memory is well-understood, routine, conventional computer function MPEP 2106.05(d). It is also noted that such elements as claimed with respect to artificial intelligence were not expressed to confer a technological improvement to a technical problem.
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.
Claims 6 and 14 are 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.
Claims 6 and 14 recites the limitation "the highest probability value" in line 1 and “the probability vector” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4, 7, 9-12, 15, 17-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Wey (US 2020/0000562).
A computer-implemented method for generating dental restoration associated with dental model of dentition, the method comprising receiving, with one or more computing devices, a patient scan data representing at least a portion of a patient’s dentition (“known 3D model of the dental situation”); and generating, using a trained deep neural network, an occlusal portion of a dental prosthesis for a preparation site, the preparation site comprising a margin line ([0030]-[0032]; full restoration is generated and therefore the occlusal portion thereof is generated; Fig. 1 shows scanning of the preparation sites [13 and 14] which include the margin line where the restoration meets the prepared tooth). With respect to claim 2, wherein the occlusal portion comprises an occlusal surface (occlusal surfaces seen in Fig. 1 near 20 for instance). With respect to claim 3, wherein the occlusal surface comprises one or more selected from the group consisting of a mesiobuccal cusp, buccal grove, distobuccal cusp, distal cusp, distobuccal groove, distal pit, lingual groove, mesiolingual cusp ([0026] for instance discusses buccal direction and occlusal direction which would be for molars having these features). With respect to claim 4, further comprising generating, using the trained deep neural network, a sidewall between the generated occlusal portion and the margin line of the preparation site (lingual and labial portions of restoration shown in Fig. 1 extending from an occlusal surface to the margin line). With respect to claim 7, wherein the occlusal portion comprises a crown, an inlay, a bridge or an implant ([0008]).
System claims 9-12, 15 are rejected similarly to the above with the use of a processor and a non-transitory computer-readable storage medium (computer 7 has these components).
Claims 17-19 are rejected similarly to the above.
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.
Claims 5 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Wey.
Wey discloses the device as previously described above and shows using a collection of a large number of 3D models ([0028]), and mapping sidewalls of technician-generated dental prostheses to the generated occlusal portion and the margin line ([0030] includes “shape of the preparation” in the data which would include the sidewalls mapped to occlusal portions since the restorations encompass this structure as seen in Fig. 1), but fails to show explicitly that thousands of data points are utilized.
The Office takes official notice that neural network training utilizes large numbers of data points to encompass as many situations as possible, including thousands or more. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Wey’s method by including thousands of data points in order to provide a sufficient amount of data points for learning many dental situations.
Claims 6 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Wey in view of Golay (US 2016/0038092).
Wey discloses the device as previously described above, but fails to show wherein a sidewall having the highest probability value (in the probability vector) can be selected as a base model in which the sidewall between occlusal surface and the margin line will be generated.
Golay similarly teaches the use of neural networks/collection of data in the same manner wherein probability values (which would be within a probability vector) can be assigned/selected ([0008], [0018], [0021]-[0022]). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Wey’s method by utilizing probability values of a probability vector as taught by Golay for the restorations of Wey in order to improve results and perform better training with weighted teaching data.
Claims 8, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wey in view of Yao et al. (US 2021/0201078).
Wey discloses the device as previously described above, but fails to show the trained deep neural network comprises a generative adversarial network (GAN).
Yao similarly teaches the training of deep neural networks wherein a generative adversarial network (GAN) may be implemented ([0191], [0199]). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Wey’s method by incorporating a GAN as taught by Yao in order to improve training of the deep neural network ([0191]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW NELSON whose telephone number is (571)270-5898. The examiner can normally be reached on Monday-Friday 7:30am-5:00pm EDT.
If attempts to reach the examiner by telephone are unsuccessful, please contact the examiner’s supervisor, Eric Rosen, at (571) 270-7855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MATTHEW M NELSON/Primary Examiner, Art Unit 3772