Prosecution Insights
Last updated: April 19, 2026
Application No. 18/512,018

METHOD AND SYSTEM FOR CALCULATING PARAMETERS IN LARYNX IMAGE WITH ARTIFICIAL INTELLIGENCE ASSISTANCE

Non-Final OA §102§112
Filed
Nov 17, 2023
Examiner
THIRUGNANAM, GANDHI
Art Unit
2672
Tech Center
2600 — Communications
Assignee
Changhua Christian Medical Foundation Changhua Christian Hospital
OA Round
1 (Non-Final)
74%
Grant Probability
Favorable
1-2
OA Rounds
3y 7m
To Grant
86%
With Interview

Examiner Intelligence

Grants 74% — above average
74%
Career Allow Rate
413 granted / 559 resolved
+11.9% vs TC avg
Moderate +12% lift
Without
With
+12.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
42 currently pending
Career history
601
Total Applications
across all art units

Statute-Specific Performance

§101
9.6%
-30.4% vs TC avg
§103
35.8%
-4.2% vs TC avg
§102
21.5%
-18.5% vs TC avg
§112
27.1%
-12.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 559 resolved cases

Office Action

§102 §112
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 Interpretation The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: input unit, processing unit, output unit in claim 9-12 Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. 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 1-12 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. A broad range or limitation together with a narrow range or limitation that falls within the broad range or limitation (in the same claim) may be considered indefinite if the resulting claim does not clearly set forth the metes and bounds of the patent protection desired. See MPEP § 2173.05(c). In the present instance, claim 1 recites the broad recitation “training a model”, and the claim also recites “training a deep learning object detection software by a plurality of larynx images with a manually marked glottis image region to extract a glottis image from a larynx image received and training a deep learning image recognition and segmentation software by a plurality of glottis images with a manually marked membranous glottal gap to recognize a membranous glottal gap in a glottis image received; the membranous glottal gap includes structural features of a left vocal fold, a right vocal fold, and an anterior commissure; “ which is the narrower statement of the range/limitation. The claim(s) are considered indefinite because there is a question or doubt as to whether the feature introduced by such narrower language is (a) merely exemplary of the remainder of the claim, and therefore not required, or (b) a required feature of the claims. Similarly Claim 1 recites “receiving a larynx image: receiving a larynx image, a plurality of larynx images captured frame-by-frame, or a larynx video that is captured when vocal folds are in a phonating state; “ “recognizing a glottis image: extracting at least one glottis image from the larynx image, the plurality of larynx images, or the larynx video by the deep learning object detection software; recognizing a membranous glottal gap in the glottis image: “ “obtaining a medical parameter: performing image processing of edge detection and image patching on the at least one membranous glottal gap filter to clearly outline a membranous glottal gap in the at least one membranous glottal gap filter and obtaining a medical parameter of a plurality of vocal fold anatomies from the clearly outlined membranous glottal gap in the at least one membranous glottal gap filter.” For purpose of Examination, the Examiner is using the narrow limitations. Claim 1 and 9 recites “image patching”. This is not a standard term in the art. Applicant’s specification fails to further define this term. It is not clear what this operation accomplishes. Claims 2-8, 10-12 are rejected as dependent upon a rejected 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1-4, 9-12 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kist(“A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis”) Kist discloses 1. A method for calculating parameters in a larynx image with an artificial intelligence assistance, comprising: training a model: training a deep learning object detection software by a plurality of larynx images with a manually marked glottis image region to extract a glottis image from a larynx image received and training a deep learning image recognition and segmentation software by a plurality of glottis images with a manually marked membranous glottal gap to recognize a membranous glottal gap in a glottis image received; the membranous glottal gap includes structural features of a left vocal fold, a right vocal fold, and an anterior commissure; (Kist, see pg. 1894(above), “ automatically propose a rectangular ROI around the glottis throughout the video using a deep neural network (See Figure 5)) that was trained on BAGLS data set”;) receiving a larynx image: receiving a larynx image, a plurality of larynx images captured frame-by-frame, or a larynx video that is captured when vocal folds are in a phonating state; (Kist, pg. 1890, Fig. 1, PNG media_image1.png 248 618 media_image1.png Greyscale , Video data and soundwaves) recognizing a glottis image: extracting at least one glottis image from the larynx image, the plurality of larynx images, or the larynx video by the deep learning object detection software; (Kist, pg. 1894, PNG media_image2.png 268 306 media_image2.png Greyscale , “user to select ROI for further processing” ) recognizing a membranous glottal gap in the glottis image: recognizing a membranous glottal gap in the at least one glottis image by the deep learning image recognition and segmentation software and outputting at least one membranous glottal gap filter corresponding to the at least one glottis image by the deep learning image recognition and segmentation software; and (Kist, see pg. 1894(above), “ automatically propose a rectangular ROI around the glottis throughout the video using a deep neural network (See Figure 5)) that was trained on BAGLS data set”;pg. 1895-1896 “ PNG media_image3.png 162 298 media_image3.png Greyscale PNG media_image4.png 256 310 media_image4.png Greyscale ”, the segmentation maps reads on the filter ) obtaining a medical parameter: performing image processing of edge detection and image patching (Kist, pg. 1898, PNG media_image5.png 430 310 media_image5.png Greyscale , see points P & A ) on the at least one membranous glottal gap filter to clearly outline a membranous glottal gap in the at least one membranous glottal gap filter and obtaining a medical parameter of a plurality of vocal fold anatomies from the clearly outlined membranous glottal gap in the at least one membranous glottal gap filter. (Kist, pg. 1899, PNG media_image6.png 188 310 media_image6.png Greyscale ) Kist discloses 2. The method as claimed in claim 1, wherein in step of obtaining a medical parameter, the medical parameter obtained is a normalized membranous glottal gap area; a membranous glottal gap area of the at least one glottis image is calculated from the clearly outlined membranous glottal gap; a vocal fold length is obtained from the same clearly outlined membranous glottal gap; the vocal fold length is a straight-line distance from the left vocal fold to the anterior commissure or from the right vocal fold to the anterior commissure; the normalized membranous glottal gap area is calculated from the membranous glottal gap area and the vocal fold length. (These measurements are well-known in the art) Kist discloses 3. The method as claimed in claim 1, wherein in step of obtaining a medical parameter, the medical parameter obtained is an amplitude of vocal fold vibration; the amplitude of vocal fold vibration is a longest distance from a linkage of the left vocal fold or the right vocal fold and the anterior commissure during vocal fold adduction to a side edge of the membranous glottal gap in a direction perpendicular to the linkage. (These measurements are well-known in the art) Kist discloses 4. The method as claimed in claim 2, wherein after step of obtaining a medical parameter, performing step of preparing a report and a graph: preparing a graph with a horizontal axis of a capturing time or a frame order and a vertical axis of the normalized membranous glottal gap area. (This limitation is well-known in the art) Claims 9 and 10 are rejected under similar grounds as claim 1. Kist discloses 11. The system as claimed in claim 9, wherein the at least one medical parameter is a normalized membranous glottal gap area or an amplitude of vocal fold vibration. (These measurements are well-known in the art) Kist discloses 12. The system as claimed in claim 9, wherein the medical image is a plurality of larynx image captured frame-by-frame; the at least one medical parameter is a normalized membranous glottal gap area; the medical parameter and image report comprises a graph, wherein the graph is a coordinate graph with a horizontal axis of a frame order and a vertical axis of the normalized membranous glottal gap area. (These measurements are well-known in the art) Allowable Subject Matter Claims 5-8 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to GANDHI THIRUGNANAM whose telephone number is (571)270-3261. The examiner can normally be reached M-F 8:30-5PM. 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, Sumati Lefkowitz can be reached at 571-272-3638. 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. /GANDHI THIRUGNANAM/Primary Examiner, Art Unit 2672
Read full office action

Prosecution Timeline

Nov 17, 2023
Application Filed
Jan 09, 2026
Non-Final Rejection — §102, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12597135
SYSTEMS AND METHODS FOR UPDATING A GRAPHICAL USER INTERFACE BASED UPON INTRAOPERATIVE IMAGING
2y 5m to grant Granted Apr 07, 2026
Patent 12561963
CROSS-MODALITY NEURAL NETWORK TRANSFORM FOR SEMI-AUTOMATIC MEDICAL IMAGE ANNOTATION
2y 5m to grant Granted Feb 24, 2026
Patent 12555291
METHOD FOR AUTOMATED REGULARIZATION OF HYBRID K-SPACE COMBINATION USING A NOISE ADJUSTMENT SCAN
2y 5m to grant Granted Feb 17, 2026
Patent 12541869
GRAIN FLAKE MEASUREMENT SYSTEM, GRAIN FLAKE MEASUREMENT METHOD, AND GRAIN FLAKE COLLECTION, MOVEMENT, AND MEASUREMENT SYSTEM
2y 5m to grant Granted Feb 03, 2026
Patent 12525007
TRAINING METHOD AND ELECTRONIC DEVICE
2y 5m to grant Granted Jan 13, 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

1-2
Expected OA Rounds
74%
Grant Probability
86%
With Interview (+12.3%)
3y 7m
Median Time to Grant
Low
PTA Risk
Based on 559 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