Prosecution Insights
Last updated: April 19, 2026
Application No. 18/508,896

METHOD FOR ANALYZING NEURONAL PATTERNS IN GOLGI-STAINED IMAGES

Final Rejection §103§112
Filed
Nov 14, 2023
Examiner
PARK, SOO JIN
Art Unit
2675
Tech Center
2600 — Communications
Assignee
Leica Microsystems Cms GmbH
OA Round
2 (Final)
82%
Grant Probability
Favorable
3-4
OA Rounds
2y 8m
To Grant
99%
With Interview

Examiner Intelligence

Grants 82% — above average
82%
Career Allow Rate
589 granted / 720 resolved
+19.8% vs TC avg
Strong +17% interview lift
Without
With
+17.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
15 currently pending
Career history
735
Total Applications
across all art units

Statute-Specific Performance

§101
9.0%
-31.0% vs TC avg
§103
37.3%
-2.7% vs TC avg
§102
26.3%
-13.7% vs TC avg
§112
19.3%
-20.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 720 resolved cases

Office Action

§103 §112
DETAILED ACTION In response to the amendment filed on 01/09/2026, all the amendment to the claims have been entered and the action follows: 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 § 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. Claim 21 is 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. Regarding claim 21, the limitation “off-premise” renders the claim indefinite. The dictionary meaning of “off-premise” is “away from or outside of a building or the area of land that it is on”, however, the applicant’s specification does not define what is considered “a building or the area of land that it is on”. Since there is no defined boundary that clearly distinguishes what is considered “off-premise” vs on-premise, the metes and bounds of the claim would not have been obvious to one of ordinary skill in the art. 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 1, 2, 4, 5, 10-16, 20, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Yan et al. (“Automated and accurate detection of soma location and surface morphology in large-scale 3D neuron images”) in view of Rodriguez et al. (“Three-dimensional neuron tracing by voxel scooping”). Regarding claim 1, Yan discloses: obtaining a first data set with Golgi-stained neuronal structures (see p2 “Imaging data”, obtaining initial data of a Golgi-stained mouse brain); based on the first data set, determining a first auxiliary data set, AR1, based on a first type of neuronal structure (see p2 “Method Overview”, p3-4 “Soma Location in Local Sub-stacks”, and p4 “Fusion of repeatedly detected Somas”, based on the initial data, detecting soma features, as shown in fig 4D); analyzing AR1 with a first method to identify information related to the first type of neuronal structure in AR1 (see p4 “Fusion of repeatedly detected Somas”, analyzing the soma features using the OTSU method, to acquire soma locations, as shown in fig 4E). However, Yan does not disclose: based on the first data set, determining a second auxiliary data set, AR2, based on a second type of neuronal structure; analyzing AR2 with a second method to identify information related to the second type of neuronal structure in AR2; and generating a second data set with the identified information related to the first and second type of neuronal structures (i.e., Yan discloses detecting somas, however, no other neuronal structures). In a similar field of endeavor of detecting neural structures in a 3D Golgi-stained brain data, Rodriguez discloses: based on the first data set, determining a second auxiliary data set, AR2, based on a second type of neuronal structure (see sections 2.2-2.4, based on initial data of a Golgi-stained mouse brain, determining a dendrite seed voxel; and see section 4, wherein the seed voxel is placed in a soma); analyzing AR2 with a second method to identify information related to the second type of neuronal structure in AR2 (see section 2.4, further analyzing the dendrite seed voxel using voxel scooping, to acquire dendrite structure); and generating a second data set with the identified information related to the first and second type of neuronal structures (see fig 4D, generating a model of a neuron, as shown in fig 4D, based on and including the soma locations and the acquired dendrite structure). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Yan with Rodriguez, and detect somas, as disclosed by Yan, and detecting dendrites attached to the soma by placing a seed voxel in the soma, as disclosed by Rodriguez, for the purpose of obtaining a complete model of a neuron in an accurate and efficient manner (see Rodriguez Abstract). Regarding claim 2, Yan and Rodriguez further disclose: wherein the first data set comprises a 2D or 3D information of neuronal structures (see Yan fig 1B and Rodriguez section 1, the initial data is in 3D). Regarding claim 4, Yan and Rodriguez further disclose: wherein the first type of neuronal structure is a soma (see rejection of claim 1, soma features analyzed using the OTSU method). Regarding claim 5, Yan and Rodriguez further disclose: wherein the second type of neuronal structure is a dendrite (see rejection of claim 1, dendrite seed analyzed using the voxel scooping). Regarding claim 10, Yan and Rodriguez further disclose: wherein AR1 is analyzed by Otsu’s method (see rejection of claim 1, soma features analyzed using the OTSU method). Regarding claim 11, Yan and Rodriguez further disclose: wherein AR2 is analyzed by voxel scooping (see rejection of claim 1, dendrite seed voxel further analyzed using voxel scooping). Regarding claim 12, Rodriguez further disclose: identifying one or more third neuronal structures attached to dendrites (see section 2.5, determining short branches as dendritic spines for exclusion). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further determine dendritic spines for exclusion, as disclosed by Rodriguez, for the purposes of extracting an accurate dendritic centerline (see Rodriguez section 2.5). Regarding claim 13, Yan and Rodriguez further disclose: assigning an identified neuronal structure to an identified second neuronal structure, and/or to a third neuronal structure (see rejection of claim 1, dendrite seed voxel is placed in the soma). Regarding claim 14, Yan and Rodriguez further disclose wherein the second data set equals in at least one of the following parameters with the first data set: a dimension, a resolution, a format (see Yan fig 1B and 5B and Rodriguez fig 4D, 3D initial data and 3D model are both in 3D format). Regarding claim 15, Yan and Rodriguez further disclose: device for identifying neuronal patterns in an image, configured to: execute a method according to claim 1; and/or interface with a device, for interacting with a method according to claim 1 (see Yan and Rodriguez, an inherent computer). Regarding claim 16, Yan and Rodriguez further disclose: wherein the first neuronal structure comprises a soma, the second structure comprises a dendrite, and the third neuronal structure comprises a spine (see rejection of claim 13, soma, dendrite, and spine). Regarding claim 20, Yan and Rodriguez further disclose: wherein the one or more third neuronal structures comprises spine structures (see rejection of claim 12, dendrite spines). Regarding claim 21, Yan and Rodriguez further disclose: wherein the device comprises an off-premise device (see rejection of claim 15, the inherent computer). Allowable Subject Matter Claims 3, 6-9, and 17-19 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. Response to Arguments Arguments regarding 112(b) rejection In view of the claim amendments, the 112(b) rejection of claims 6-9, 12, 13, and 15 have been withdrawn. However, newly added claim 21 is rejected under 112(b). Arguments regarding 103 rejection Applicant's arguments filed 01/09/2026 have been fully considered but they are not persuasive. Regarding claim 1, the applicant argues that Yan and Rodriguez fail to disclose the subject matter of the claim, specifically because: i) Yan only detects soma features (AR1) and not dendrite features (AR2). Yan indeed only discloses detecting soma features. However, while Yan only detects soma features (AR1), Rodriguez discloses using such soma features (AR1) to further derive dendrites (AR2) from the same type of image Yan is based on, which reads on the claim. ii) Rodriguez’s generated clusters are not auxiliary datasets derived from the initial image volume. The examiner respectfully disagrees. Yan discloses automatically deriving soma features based on 3D Golgi-stained brain images, while Rodriguez discloses deriving dendrite features from manually derived soma features based on 3D Golgi-stained brain images (i.e., the same type of images used by Yan to derive the soma features), therefore, Yan in view of Rodriguez discloses automatically deriving soma features based on 3D Golgi-stained brain images and further deriving dendrite features based on those derived soma features, as both features are derivable from the same type of image. iii) Rodriguez does not disclose AR2, therefore, Rodriguez does not disclose a second method to analyze the AR2 The examiner respectfully disagrees. As explained above, Rodriguez discloses dendrite features (AR2), which is analyzed in a different manner from Yan’s soma features. iv) Neither Yan nor Rodriguez discloses generating a final output containing information regarding both soma and dendrites. The examiner respectfully disagrees. Rodriguez’s dendrite seed voxel is placed at soma locations. Rodriguez’s fig 1 and 4, for example, displays a generated model of a neuron including such soma locations in addition to the dendrites. For the above reasons, the rejection under 103 has been maintained. Conclusion THIS ACTION IS MADE FINAL. 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 SJ PARK whose telephone number is (571)270-3569. The examiner can normally be reached M-F 8:00 AM - 5:00 PM. 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, ANDREW MOYER can be reached at 571-272-9523. 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. /SJ Park/Primary Examiner, Art Unit 2675
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Prosecution Timeline

Nov 14, 2023
Application Filed
Oct 07, 2025
Non-Final Rejection — §103, §112
Jan 09, 2026
Response Filed
Feb 26, 2026
Final Rejection — §103, §112 (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
82%
Grant Probability
99%
With Interview (+17.3%)
2y 8m
Median Time to Grant
Moderate
PTA Risk
Based on 720 resolved cases by this examiner. Grant probability derived from career allow rate.

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