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 .
Priority
Applicant’s claim of priority based on continuation to Application No. 18/504,769, filed on November 8, 2023, now US Patent No. 12,154,321, which claims the benefit of and priority to U.S. provisional patent Application No. 63,424,098, filed on November 9, 2022, is acknowledged.
Information Disclosure Statement
The information disclosure statements (“IDS”) filed on 10/17/2024 and 05/28/2025 were reviewed and the listed references were noted.
Drawings
The 18-page drawings have been considered and placed on record in the file.
Status of Claims
Claims 21-40 are pending. Claims 1-20 are canceled.
Claim Objections
Independent Claims 21 and 31 are objected to because of the following informalities: in both Claims 21 and 31, in the 9th line, the term “the localized” must be corrected to “the localized information” in order to be consistent with the rest of limitations within the claims. In addition, Examiner has noted that Claim 34 recites its dependency from Claim 33. However, the method Claim 24, which recites a similar limitation to the one in Claim 34, recites its dependency from independent Claim 21.
Appropriate corrections are required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper time-wise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b). In order to expedite the processing/approval of the terminal disclaimer, Applicants may choose to file an electronic terminal disclaimer (eTerminal Disclaimer) by referring to the following website:
http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp
Claims 21-40 of the instant application are rejected on the ground of nonstatutory double patenting as being unpatentable over claims of the parent U.S. Patent No. 12,154,321. Although the conflicting claims are not identical, they are not patentably distinct from each other, because claims of the instant application are generic to all that is recited in claims of the parent U.S. Patent No. 12,154,321. For example, the following chart compares Claim 21 of the instant application with Claim 1 of the parent U.S. Patent No. 12,154,321.
Instant Application
Patent Application No. 12,154,321
Claim 21. A method for creating an interpretable model from patient images, the method comprising:
receiving, via a processor, imaging data of a region of interest of a patient;
processing, via the processor, the imaging data to provide localized information;
transforming, via the processor, a plurality of cross section at various locations in the region of interest from a first coordinate system to a second coordinate system causing for each cross section, mechanistic relationships to be emphasized, while reducing nuisance variation for spurious information;
creating, via the processor, a structured representation of the localized based on the transformed plurality of cross sections in the region of interest, wherein at least some of the localized information is identified as significant; and
using, via the processor, the structured representations for the purpose of training to create the interpretable model, wherein the significant localized information contributes to the model inference.
Claim 1. A method for creating an interpretable model from patient images, the method comprising:
receiving, via a processor, imaging data of a region of interest of a patient;
processing, via the processor, the imaging data to provide spatially-localized or temporally-localized information;
creating, via the processor, a structured representation of the spatially-localized or temporally-localized information that causes at least some of the spatially-localized or temporally-localized information to be indicated as significant spatially-localized or temporally-localized information, wherein creating the structure representation includes:
determining a plurality of cross sections at various location in the region of interest;
ii)unwrapping each of the plurality of cross sections into two one dimensional vectors to create a plurality of two one dimensional vectors;
iii)concatenating the plurality of two one dimensional vectors to create the structured representation of the spatially-localized or temporally localized information; and
using, via the processor, the structured representations for the purpose of training to create the interpretable model, wherein the significant spatially-localized or temporally-localized information contributes to the model inference.
Allowable Subject Matter
The claims of the instant application are not rejected over prior art and will be allowed if the above-described rejection of claims based on non-statutory double patenting is resolved. The following is a statement of reasons for the indication of allowable subject matter: consider Claim 21, the closest prior art reference, Min et al. (US 2021/0319558 - IDS) discloses: “A method for creating an interpretable model from patient images, the method comprising: receiving, via a processor, imaging data of a region of interest of a patient” (Min, Paragraphs [0008] and [0014], the computer system, i.e., processor, Paragraph [0186], wherein a medical image of a subject is acquired); “processing, via the processor, the imaging data to provide localized information” (Min, Paragraph [0014], wherein segmenting the medical image of the subject by a computer system is disclosed to produce the coronary arteries; and Paragraph [0187], wherein the system can identify one or more arteries in the subject’s coronary region); “a structured representation of the localized (Min, Paragraph [0189], the automatic or dynamic determination of vascular morphology parameters and/or plaque parameters, which causes indication of significantly localized information). In an analogous field of endeavor, Neumann et al. (US 2020/0356864 - IDS) discloses “ameliorative process label learner may generate the at least an ameliorative output by creating a second-machine learning model using the second training set relating prognostic labels to ameliorative labels. Second machine-learning model may use ameliorative label to generate at least an ameliorative output. Ameliorative output may be generated as a function of a classification of the at least a prognostic output. Prognostic output may be classified by any schematic as described above in reference to FIGS. 1-21. Second machine learning-model may use models to create correlations relating a prognostic output such as high blood pressure to an ameliorative label with an alimentary recommendation that avoids salty foods so as to reduce high blood pressure. In yet another example, machine-learning models may create correlations relating a prognostic output such as coronary artery occlusion to an ameliorative label such as angioplasty” (Neumann, Paragraph [0142]). However, none of the cited prior art references, alone or in combination, provides a motivation to teach the ordered combination of “transforming, via the processor, a plurality of cross section at various locations in the region of interest from a first coordinate system to a second coordinate system causing for each cross section, mechanistic relationships to be emphasized, while reducing nuisance variation for spurious information; creating, via the processor, a structured representation of the localized based on the transformed plurality of cross sections in the region of interest, wherein at least some of the localized information is identified as significant; and using, via the processor, the structured representations for the purpose of training to create the interpretable model, wherein the significant localized information contributes to the model inference.” Independent Claim 31 includes the above-described allowable subject matter, and therefore, not rejected over prior art. Dependent Claims 22-30 and 32-40, which depend from independent Claims 21 and 31, respectively, inherently include the above-discussed allowable subject matter, and therefore not rejected over prior art.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance”.
Conclusion and Contact Information
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure: Ishikawa et al. (US 2011/0262015), Abstract and Paragraph [0011], where rigid transformation is disclosed that involves a cross section image of the region of interest and discussions of the first and second coordinate systems.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Siamak HARANDI whose telephone number is (571)270-1832. The examiner can normally be reached Monday - Friday 9:30 - 6:00 ET.
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/Siamak Harandi/Primary Examiner, Art Unit 2662
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