Prosecution Insights
Last updated: April 19, 2026
Application No. 18/297,112

METHOD AND APPARATUS FOR AUTOENCODER-BASED ANOMALY DETECTION IN MEDICAL IMAGING SYSTEMS

Final Rejection §103
Filed
Apr 07, 2023
Examiner
NGUYEN, LAM S
Art Unit
2853
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Canon Medical Systems Corporation
OA Round
2 (Final)
79%
Grant Probability
Favorable
3-4
OA Rounds
2y 9m
To Grant
79%
With Interview

Examiner Intelligence

Grants 79% — above average
79%
Career Allow Rate
1093 granted / 1391 resolved
+10.6% vs TC avg
Minimal +1% lift
Without
With
+0.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
61 currently pending
Career history
1452
Total Applications
across all art units

Statute-Specific Performance

§101
2.5%
-37.5% vs TC avg
§103
45.9%
+5.9% vs TC avg
§102
33.7%
-6.3% vs TC avg
§112
8.1%
-31.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1391 resolved cases

Office Action

§103
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 . 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(s) 1-3, 5-8, 13, 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vogtmeier (WO 2022/096386) in view of Schmitt et al. (US 2021/0110262). Regarding to claims 1, 18, 20: Vogtmeier discloses a method for detecting an anomaly related to a medical imaging device, the method comprising: acquiring data from a plurality of detectors of the medical imaging device (FIG. 1, step S1 and S3 and page 10, lines 1-13: The measurement data); applying the acquired data comprising splitting, based on a predetermined criterion, the acquired data into a first group of data and a second group of data, applying and processing the first group of data to obtain first outputs, and applying and processing the second group of data to obtain second outputs (page 13, lines 1-13 and FIG. 1: The first data set and the second data set are acquired (step S1, S3) at different operation modes, and processed to be output at step S2, S4); and detecting the anomaly related to the medical imaging device based on a difference between the first outputs and the second outputs (page 13, lines 13-22: The data sets, after being processed, are compared and validated (steps S5-S6) whether the data sets differ from each other to generate a maintenance prediction information). Vogtmeier however does not teach wherein processing the first data set and the second data set by a first autoencoder. Schmitt et al. discloses a method for detecting an anomalous operating status of a technical system comprising acquiring data from the technical system and applying the data to an autoencoder for processing to determine the anomalous operating status (paragraph [0031]: Using auto-encoder neural network to obtain good performance for anomaly scores). Therefore, it would have been obvious for one having ordinary skill in the art before the effective filing date of the claimed invention to modify Vogtmeier’s method to use an auto-encoder to process the data sets to detect the anomaly as disclosed by Schmitt, because of its very high performance that exceeds the performance state of art in the anomaly detection (paragraphs [0030]-[0031]). Schmitt also discloses the following claims: Regarding to claim 2: wherein the first autoencoder comprises an encoder (FIG. 9, elements ENCODER) configured to generate latent vectors (FIG. 9: LATENT REPRESENTATION), and a decoder (FIG. 9, elements DECODER) configured to reconstruct data from the generated latent vectors, and the step of detecting the anomaly further comprises detecting, based on the generated latent vectors or the reconstructed data, the anomaly related to the technical device (FIG. 9 shows the anomaly scores ASa and ASb generated from the outputs of the latent vector and decoder). Regarding to claims 3, 8, 19: further comprising: training the first autoencoder based on a training dataset generated from the data acquired from the plurality of detectors, wherein the training dataset comprises a first training dataset and a second training dataset (FIG. 1 shows the preparatory training step from the data samples characterizing anomalous operation (first dataset) and normal operation (second dataset)). Regarding to claim 13: wherein the detecting step further comprises detecting the anomaly: by means of direct analysis of the outputs from the first autoencoder; by means of clustering of the outputs from the first autoencoder; or by means of a power spectrum analysis of the outputs from the first autoencoder (FIG. 9 shows the anomaly score Asa calculated from the output of the decoder). Vogtmeier also discloses the following claims: Regarding to claim 5-7: wherein the predetermined criterion is an operation condition/processing method/a time of the medical imaging device, the first and second groups of data correspond to a first operating condition/processing method/a first time and a second condition/processing method/a second time, respectively, and the first and second operating conditions/processing methods/times are different from each other (page 13, lines 1-15: The data sets are acquired at different operating modes including condition and processing and times). Response to Arguments Applicant’s arguments with respect to the claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Claim 1 even though is amendment to include the original claim 4, the scope of the amended claim 1 is not identical to that of the original claim 4 previously indicated as allowable. 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 LAM S NGUYEN whose telephone number is (571)272-2151. 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, DOUGLAS RODRIGUEZ, can be reached on 571-431-0716. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /LAM S NGUYEN/ Primary Examiner, Art Unit 2853
Read full office action

Prosecution Timeline

Apr 07, 2023
Application Filed
Sep 18, 2025
Non-Final Rejection — §103
Dec 23, 2025
Response Filed
Mar 08, 2026
Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12599155
SYSTEM AND METHOD OF NON-LINEAR COOK TIME ESTIMATION
2y 5m to grant Granted Apr 14, 2026
Patent 12590890
SAMPLE GAS ANALYSIS DEVICE, SAMPLE GAS ANALYSIS METHOD, AND PROGRAM FOR SAMPLE GAS ANALYSIS
2y 5m to grant Granted Mar 31, 2026
Patent 12589490
CAPABILITIES FOR ERROR CATEGORIZATION, REPORTING AND INTROSPECTION OF A TECHNICAL APPARATUS
2y 5m to grant Granted Mar 31, 2026
Patent 12579661
METHODS, SYSTEMS, AND STORAGE MEDIUMS FOR FLOW VELOCITY DETECTION
2y 5m to grant Granted Mar 17, 2026
Patent 12578394
BATTERY MANAGEMENT APPARATUS AND METHOD
2y 5m to grant Granted Mar 17, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
79%
Grant Probability
79%
With Interview (+0.7%)
2y 9m
Median Time to Grant
Moderate
PTA Risk
Based on 1391 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month