Prosecution Insights
Last updated: April 19, 2026
Application No. 17/925,755

METHOD FOR DETERMINING AN ABLATION REGION BASED ON DEEP LEARNING

Final Rejection §101
Filed
Nov 16, 2022
Examiner
KY, KEVIN
Art Unit
2671
Tech Center
2600 — Communications
Assignee
Quantum Surgical
OA Round
2 (Final)
76%
Grant Probability
Favorable
3-4
OA Rounds
2y 6m
To Grant
99%
With Interview

Examiner Intelligence

Grants 76% — above average
76%
Career Allow Rate
420 granted / 549 resolved
+14.5% vs TC avg
Strong +25% interview lift
Without
With
+25.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
33 currently pending
Career history
582
Total Applications
across all art units

Statute-Specific Performance

§101
17.6%
-22.4% vs TC avg
§103
46.5%
+6.5% vs TC avg
§102
20.8%
-19.2% vs TC avg
§112
9.9%
-30.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 549 resolved cases

Office Action

§101
DETAILED ACTION 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 and 3-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. The claim(s) recite(s) limitations that fall under the grouping of abstract idea of “Mental Processes”, e.g. concepts performed in the human mind (such as observation, evaluation and judgement) and “Mathematical Concepts”, such as mathematical relationships and algorithms (step 2A, prong one). For example, while the steps of acquiring a post-operative medical image involves data gathering, the claimed abstract idea lies in the subsequent evaluation and analysis of image data. In particular, the steps of determining an outline of an ablation region corresponds to observation and evaluation of image features (e.g. identifying boundaries or regions of interest), which can be practically performed in the human mind or with the aid of pen and paper, even if the claims recites that such steps are performed automatically. The step of automatically determining an outline of the ablation region via a machine learning method is also considered a mathematical concept implemented on a computer, as neural network processing inherently involves mathematical computations. Furthermore, the training phase is also considered a mathematical concept. While a neural network is cited, it is still at a high level of generality. The claims do not specify how the determining of an outline is performed; any generic neural network could be used. Support for this interpretation comes from “Kaavo Inc. v. Amazon. com, Inc., 323 F. Supp. 3d 630 - Dist. Court, D. Delaware 2018” and other similar court documents, in which a neural network is cited at a similar level of generality. Under step 2A, prong two, this judicial exception is not integrated into a practical application. The claim merely applies a training routine using a generic machine learning techniques without reciting any specific improvements to computer functionality or a particular technological solution. Thus, the claims are direct to an abstract idea implemented on a generic computing system. Under step 2B, the claims does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because these are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d). The claims do not include an inventive concept that is sufficient to transform the abstract idea into a patent-eligible application. Dependent claims 3-21 are considered an abstract idea for the same reasonings as listed above (e.g. mental process, mathematical concept), or the claims are not considered to be significantly more. Regarding claim 3, 13-15 and 18-19, the claims merely recite different training data, image registration of segmentation, and pre-processing steps. The claims do not add any specifical technical improvement or unconventional features. Regarding claims 4-10, the claims merely recite mathematical concepts (e.g. computing geometric or statistical relationships), or mental processes (e.g. evaluating recurrence risk or determining recurrence position). The claims also do not add any specifical technical improvement or unconventional features. Regarding claim 11-12, the claims merely recite routine abstract mathematical image operations. They do not result in a practical application. Regarding claims 16-17, the claims merely recite mental or mathematical processes of determining a ablation mask and a path for a medical instrument. Regarding claims 20-21, while a device is claimed, merely reciting a generic computer or system performing abstract functions does not render the claim patent-eligible. Response to Arguments Applicant's arguments filed 1/7/2026 have been fully considered but they are not persuasive. Regarding claims 1 and 3-21, the applicant argues that the claims are patent eligible under 35 U.S.C. 101. With respect to Step 2A, Prong One, the applicant argues that the claims do not recite a mental process and that image acquisition cannot be performed mentally. The rejection is clarified that the “acquiring” is treated as data gathering, while the abstract idea lies in the subsequent analysis of the image. In particular, determining an outline of an ablation region from an image constitutes observation and evaluation of image features, which can be practically performed in the human mind (or with pen and paper), even if the claim recites automation via a neural network. Additionally, the recited neural-network-based training and analysis inherently involve mathematical computations, and thus the claims also recite mathematical concepts rather than merely involving them. Under Step 2A, Prong Two, applicant’s argument that the claims are integrated into a practical medical workflow is not persuasive. The independent claim recites acquiring image data and generating an outline but does not require any further use of that output in a treatment or device control. Accordingly, the claim is direct to analysis of data and generation of information in a particular field of use, which does not constitute a practical application. The recited training step using images of unablated lesions amount to a specification of training data and does not provide a technological improvement. With respect to Step 2B, applicant’s arguments regarding an inventive concept are not persuasive. The claims rely on generic neural network and data selection for training, which are well-understood, routine, and conventional. The claims do not recite any specific implementation or improvement to computer functionality. Applicant’s reliance on Berkheimer and Desjardins is not persuasive, as the claims do not recite a non-conventional technical solution but instead apply known machine learning techniques to data analysis. Accordingly, the claims remain directed to a judicial exception without significantly more, and the rejection under 35 U.S.C. 101 is maintained. Conclusion 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. Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEVIN KY whose telephone number is (571)272-7648. The examiner can normally be reached Monday-Friday 9-5PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vincent Rudolph can be reached at 571-272-8243. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /KEVIN KY/Primary Examiner, Art Unit 2671
Read full office action

Prosecution Timeline

Nov 16, 2022
Application Filed
Jul 02, 2025
Non-Final Rejection — §101
Jan 07, 2026
Response Filed
Mar 24, 2026
Final Rejection — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
76%
Grant Probability
99%
With Interview (+25.3%)
2y 6m
Median Time to Grant
Moderate
PTA Risk
Based on 549 resolved cases by this examiner. Grant probability derived from career allow rate.

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