Prosecution Insights
Last updated: April 19, 2026
Application No. 18/967,330

ENDOSCOPE PROCESSOR, METHOD FOR OPERATING ENDOSCOPE PROCESSOR, AND STORAGE MEDIUM

Non-Final OA §103
Filed
Dec 03, 2024
Examiner
BRUTUS, JOEL F
Art Unit
3798
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Olympus Corporation
OA Round
1 (Non-Final)
72%
Grant Probability
Favorable
1-2
OA Rounds
3y 7m
To Grant
90%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allow Rate
922 granted / 1276 resolved
+2.3% vs TC avg
Strong +18% interview lift
Without
With
+18.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
48 currently pending
Career history
1324
Total Applications
across all art units

Statute-Specific Performance

§101
5.9%
-34.1% vs TC avg
§103
47.7%
+7.7% vs TC avg
§102
14.9%
-25.1% vs TC avg
§112
23.6%
-16.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1276 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 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 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) 1-5, 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Igarashi (Pub. No.: US 2013/0329027) in view of Kanamori (Pub. No.: US 2012/0307028). Regarding claim 1, Igarashi discloses an endoscope processor comprising: one or more processors (processor 7) comprising hardware [see fig 1, 0044], wherein the one or more processors are configured to: acquire a first image (image P1 as shown in fig 4) that is based on light in a first wavelength band (as shown in fig 2) belonging to a red band [see figs 2, 4, 15]; acquire a second image (image P2 as shown in fig 4) that is based on light in a second wavelength band (as shown in fig 2) belonging to a blue band [see figs 2, 4, 15]; generate unevenness information (thicker blood vessel) of a mucosa based on the first image (band image signal near P1(1)) [see 0070-0071, 0175, 0188] by disclosing a band image signal near P1(1) has information about a living structure such as a thicker blood vessel in a deep part [see 0070]; generate an emphasized second image in which an uneven region (relatively thick blood vessel) in the second image is emphasized based on the unevenness information and the second image [see 0068-0071, 0113] by disclosing performing emphasis processing for at least one band image signal with a low spatial frequency among the obtained multiple band image signals, a relatively thick blood vessel existing in a relatively deep part of the living mucosa is emphasized [see 0113]; generate an output image by inputting the emphasized second image to at least one of a R channel, a G channel and a B channel composing the output image [see 0055, 0071, figs 2, 4] by disclosing emphasis processing section 101a performs image processing for image emphasis of the blood vessel 61, and the color conversion processing section 101b allocates each image signal to each channel of RGB of the observation monitor 5 [see 0071]. With regards to “extracting/extract”; Igarashi discloses acquiring unevenness information (thicker blood vessel) [see 0070, 0113]; however, Igarashi doesn’t explicitly mention “extract/extracting. Nonetheless, Kanamori discloses the unevenness on the surface or an organism's organ or mucosa actually has various shapes. Models of such actual grooves are illustrated in FIGS. 9 through 12 [see 0113] and further discloses extracting groove segments (unevenness, emphasis added) from actual objects [see 0164, 0168-0169]. Therefore, it is obvious to one skilled in the art at the time the invention was filed and would have been motivated to combine Igarashi and Kanamori by extracting unevenness information; to separate unevenness information from the image. Regarding claim 2, Igarashi discloses wherein the one or more processors are configured to input the emphasized second image to the G channel of the output image [see 0071] by disclosing emphasis processing section 101a performs image processing for image emphasis of the blood vessel 61, and the color conversion processing section 101b allocates each image signal to each channel of RGB of the observation monitor 5 [see 0071]. Regarding claim 3, Igarashi discloses wherein the one or more processors are configured to acquire a third image based on light in a third wavelength band belonging to a green band [see figs 2, 4]. Regarding claim 4, Igarashi discloses wherein the one or more processors are configured to: input the emphasized second image to the G channel and the B channel of the output image, and input the third image to the R channel of the output image [see 0071, figs 2, 4] by disclosing emphasis processing section 101a performs image processing to be described later for image emphasis of the blood vessel 61, and the color conversion processing section 101b allocates each image signal to each channel of RGB of the observation monitor 5 [see 0071]. Regarding claim 5, Igarashi discloses wherein the one or more processors are configured to extract the unevenness information by calculating a high frequency component (gradually higher from fr2 toward frN) from the first image [see fig 4, 0070, 0175] by disclosing the band image signal P1(N) is an image signal with the highest spatial frequency [see 0070] and information about an uneven surface structure such as a thinner blood vessel or a gland structure in a mucosal epithelium [see 0070]. Regarding claim 8, Igarashi discloses a method comprising: acquiring a first image (image P1 as shown in fig 4) that is based on light in a first wavelength band (as shown in fig 2) belonging to a red band [see figs 2, 4, 15]; acquiring a second image (image P2 as shown in fig 4) that is based on light in a second wavelength band (as shown in fig 2) belonging to a blue band [see figs 2, 4, 15]; generating unevenness information of a mucosa based on the first image; generating an emphasized second image in which an uneven region in the second image is emphasized based on the unevenness information and the second image [see 0068-0071, 0113] by disclosing performing emphasis processing for at least one band image signal with a low spatial frequency among the obtained multiple band image signals, a relatively thick blood vessel existing in a relatively deep part of the living mucosa is emphasized [see 0113]; generating an output image by inputting the emphasized second image to at least one of: an R channel, a G channel and a B channel composing the output image [see 0071, figs 2, 4] by disclosing emphasis processing section 101a performs image processing to be described later for image emphasis of the blood vessel 61, and the color conversion processing section 101b allocates each image signal to each channel of RGB of the observation monitor 5 [see 0071]. With regards to “extracting/extract”; Igarashi discloses acquiring unevenness information (thicker blood vessel) [see 0070, 0113]; however, Igarashi doesn’t explicitly mention “extract/extracting. Nonetheless, Kanamori discloses the unevenness on the surface or an organism's organ or mucosa actually has various shapes. Models of such actual grooves are illustrated in FIGS. 9 through 12 [see 0113] and further discloses extracting groove segments (unevenness, emphasis added) from actual objects [see 0164, 0168-0169]. Therefore, it is obvious to one skilled in the art at the time the invention was filed and would have been motivated to combine Igarashi and Kanamori by extracting unevenness information; to separate unevenness information from the image. Regarding claim 9, Igarashi discloses non-transitory computer-readable storage medium storing instructions that, when executed, causes a computer to at least perform: acquiring a first image (image P1 as shown in fig 4) that is based on light in a first wavelength band (as shown in fig 2) belonging to a red band [see figs 2, 4, 15]; acquiring a second image (image P2 as shown in fig 4) that is based on light in a second wavelength band (as shown in fig 2) belonging to a blue band [see figs 2, 4, 15]; generating unevenness information of a mucosa based on the first image; generating an emphasized second image in which an uneven region in the second image is emphasized based on the unevenness information and the second image [see 0068-0071, 0113] by disclosing performing emphasis processing for at least one band image signal with a low spatial frequency among the obtained multiple band image signals, a relatively thick blood vessel existing in a relatively deep part of the living mucosa is emphasized [see 0113]; generating an output image by inputting the emphasized second image to at least one of a R channel, a G channel and a B channel composing the output image [see 0071, figs 2, 4] by disclosing emphasis processing section 101a performs image processing to be described later for image emphasis of the blood vessel 61, and the color conversion processing section 101b allocates each image signal to each channel of RGB of the observation monitor 5 [see 0071]. With regards to “extracting/extract”; Igarashi discloses acquiring unevenness information (thicker blood vessel) [see 0070, 0113]; however, Igarashi doesn’t explicitly mention “extract/extracting. Nonetheless, Kanamori discloses the unevenness on the surface or an organism's organ or mucosa actually has various shapes. Models of such actual grooves are illustrated in FIGS. 9 through 12 [see 0113] and further discloses extracting groove segments (unevenness, emphasis added) from actual objects [see 0164, 0168-0169]. Therefore, it is obvious to one skilled in the art at the time the invention was filed and would have been motivated to combine Igarashi and Kanamori by extracting unevenness information; to separate unevenness information from the image. Claim(s) 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Igarashi (Pub. No.: US 2013/0329027) in view of Kanamori (Pub. No.: US 2012/0307028) as applied to claim 1 above and further in view of Hirota (Pub. No.: US 2018/0077399). Regarding claims 6-7, Igarashi discloses scattering characteristic of living tissue is suppressed [see 0126, 0164, 0187]. Igarashi and Kanamori don’t disclose suppress a blood vessel figure in the second image by calculating a high frequency component of the second image including the blood vessel figure and subtracting the high frequency component from the second image. Nonetheless, Hirota discloses calculating a high frequency component of the second image including the blood vessel figure and subtracting (by calculating a difference, emphasis added) the high frequency component from the second image [see 0093, 0099-0100]. Therefore, it is obvious to one skilled in the art at time the invention was filed and would have been motivated to combine Igarashi, Kanamori and Hirota by calculating a high frequency component of the second image including the blood vessel figure and subtracting the high frequency component from the second image; to extract absorption information from a first image on the basis of a specific frequency component in the first image and correlation between the first image and a second image. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOEL F BRUTUS whose telephone number is (571)270-3847. The examiner can normally be reached Mon-Sat, 11:00 AM to 7:00 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, Pascal Bui-Pho can be reached at 571-272-2714. 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. /JOEL F BRUTUS/ Primary Examiner, Art Unit 3798
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Prosecution Timeline

Dec 03, 2024
Application Filed
Dec 17, 2024
Response after Non-Final Action
Dec 10, 2025
Non-Final Rejection — §103 (current)

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Prosecution Projections

1-2
Expected OA Rounds
72%
Grant Probability
90%
With Interview (+18.0%)
3y 7m
Median Time to Grant
Low
PTA Risk
Based on 1276 resolved cases by this examiner. Grant probability derived from career allow rate.

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