IP Library › Granted Patent US 12,414,681
Granted Patent B2
US 12,414,681 · App. 18/748,273 · Granted Sep 16, 2025

Endoscopy support apparatus, endoscopy support method, and computer readable recording medium

Inventors: Tatsu Kimura (Tokyo, JP); Kenichi Kamijo (Tokyo, JP); Shota Ohtsuka (Tokyo, JP); Kimiyasu Takoh (Tokyo, JP); Ikuma Takahashi (Tokyo, JP); Motoyasu Okutsu (Tokyo, JP)
Assignee: NEC CORPORATION
A61B1/045A61B1/000094G06T7/0012G06T2207/10068G06T2207/30096
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,414,681
App. No.
18/748,273
Granted
Sep 16, 2025
Kind
B2
Abstract

An endoscopy support apparatus 1 includes: an analysis information generation unit 2 that inputs image information of an imaged living body into a model, estimates a region of a target site of the living body, and generates analysis information including region information indicating the estimated region and score information indicating likeness of the region to the target site; a user information generation unit 3 that generates user information related to the user, which has been input by a user using a user interface 23 ; an image-related information generation unit 4 that generates image-related information by associating imaging date and time information, the analysis information, and the user information, for each piece of image information; and an examination management information generation unit 5 that generates examination management information by associating a plurality of pieces of the image-related information with examination information indicating an examination period.

Claims (56)

1. An endoscopy support apparatus comprising:

a processor; and

a memory storing instructions executable by the processor to:

input a plurality of pieces of image information of a living body imaged by an endoscope into a model;

for each piece of image information, estimate a region of a target site of the living body, and generate analysis information including region information indicating the estimated region and score information indicating a likeness of the region to the target site;

generate user information related to a user, which has been input by the user using a user interface;

generate image-related information by associating imaging date and time information indicating a date and time when an image was captured, the analysis information, and the user information, for each piece of image information;

generate examination management information by associating the image-related information generated for each piece of image information during an examination period with examination information identifying an examination;

cause a display of an output device to display an examination result screen indicating an examination result based on examination management information;

classify the score information for each piece of image information that lies within a score range set by the user via the examination result screen; and

cause the display to display the user information, the imaging date and time information, and the analysis information, for each piece of image information for which the score has been classified.

2. The endoscopy support apparatus according to claim 1 , wherein the instructions are executable by the processor to further:

generate user setting information used for setting output of the analysis information for each of a plurality of users.

3. The endoscopy support apparatus according to claim 2 ,

wherein the user setting information includes at least one of setting information for changing display of the region according to the score information and setting information for changing a volume according to the score information, in the examination.

4. The endoscopy support apparatus according to claim 1 ,

wherein when the processor obtains end information indicating an end of the examination, the processor generates the examination management information.

5. The endoscopy support apparatus according to claim 1 , wherein

the model is generated by machine learning, and

the examination result is optimized for the user based on a user profile included in the user information to support decision making by the user.

6. An endoscopy support method performed by a computer and comprising:

inputting a plurality of pieces of image information of a living body imaged by an endoscope into a model;

for each piece of image information, estimating a region of a target site of the living body, and generating analysis information including region information indicating the estimated region and score information indicating a likeness of the region to the target site;

generating user information related to a user, which has been input by the user using a user interface;

generating image-related information by associating imaging date and time information indicating a date and time when an image was captured, the analysis information, and the user information, for each piece of image information;

generating examination management information by associating the image-related information generated for each piece of image information during an examination period with examination information identifying an examination;

causing a display of an output device to display an examination result screen indicating an examination result based on the examination management information;

classifying the score information for each piece of image information that lies within a score range set by the user via the examination result screen; and

causing the display to display the user information, the imaging date and time information, and the analysis information, for each piece of image information for which the score has been classified.

7. The endoscopy support method according to claim 6 , further comprising

generating user setting information used for setting output of the analysis information for each of a plurality of users.

8. The endoscopy support method according to claim 6 ,

wherein the user setting information includes at least one of setting information for changing display of the region according to the score information and setting information for changing a volume according to the score information, in the examination.

9. The endoscopy support method according to claim 6 ,

wherein when end information indicating an end of the examination is obtained, the examination management information is generated.

10. The endoscopy support method according to claim 6 , wherein

the model is generated by machine learning, and

the examination result is optimized for the user based on a user profile included in the user information to support user's decision making by the user.

11. A non-transitory computer readable recording medium storing a program including instructions that cause a computer to carry out:

inputting a plurality of pieces of image information of a living body imaged by an endoscope into a model;

for each piece of image information, estimating a region of a target site of the living body, and generating analysis information including region information indicating the estimated region and score information indicating a likeness of the region to the target site;

generating user information related to a user, which has been input by the user using a user interface;

generating image-related information by associating imaging date and time information indicating a date and time when an image was captured, the analysis information, and the user information, for each piece of image information;

generating examination management information by associating the image-related information generated for each piece of image information during an examination period with examination information identifying an examination;

causing a display of an output device to display an examination result screen indicating an examination result based on the examination management information;

classifying the score information for each piece of image information that lies within a score range set by the user via the examination result screen; and

causing the display to display the user information, the imaging date and time information, and the analysis information, for each piece of image information for which the score has been classified.

12. The non-transitory computer readable recording medium according to claim 11 , wherein the instructions further cause the computer to carry out

generating user setting information used for setting output of the analysis information for each of a plurality of users.

13. The non-transitory computer readable recording medium according to claim 11 ,

wherein the user setting information includes at least one of setting information for changing display of the region according to the score information and setting information for changing a volume according to the score information, in the examination.

14. The non-transitory computer readable recording medium according to claim 11 ,

wherein when end information indicating an end of the examination is obtained, the examination management information is generated.

15. The non-transitory computer readable recording medium according to claim 11 , wherein

the model is generated by machine learning, and

the examination result is optimized for the user based on a user profile included in the user information to support decision making by the user.

Continuity (2)
Continuation 17635786
Related Publication 20240335101A1 · Oct 10, 2024
References Cited (24)
US 11450425B2 · Kamon · 2022 [cited by examiner]
US 12198798B2 · Endo · 2025 [cited by examiner]
US 20160302644A1 · Umemoto · 2016 [cited by applicant]
US 20180184881A1 · Urasaki · 2018 [cited by examiner]
US 20190192048A1 · Makino et al. · 2019 [cited by applicant]
US 20190380617A1 · Oosake · 2019 [cited by examiner]
US 20200126655A1 · Sasaki · 2020 [cited by examiner]
US 20200143936A1 · Kamon · 2020 [cited by examiner]
US 20200242766A1 · Endo · 2020 [cited by applicant]
US 20220151462A1 · Usuda · 2022 [cited by examiner]
CN 112399816A · 2021 [cited by applicant]
CN 113164010A · 2021 [cited by applicant]
EP 3590415A1 · 2020 [cited by applicant]
JP 2008079648A · 2008 [cited by applicant]
JP 2016221065A · 2016 [cited by applicant]
JP 2017056123A · 2017 [cited by applicant]
WO 2018043550A1 · 2018 [cited by applicant]
WO 2018159461A1 · 2018 [cited by applicant]
WO 2018221033A1 · 2018 [cited by applicant]
WO 2018235420A1 · 2018 [cited by applicant]
WO 2019078102A1 · 2019 [cited by applicant]
International Search Report for PCT Application No. PCT/JP2020/000647, mailed on Mar. 17, 2020. [cited by applicant]
English translation of Written opinion for PCT Application No. PCT/JP2020/000647, mailed on Jul. 21, 2022. [cited by applicant]
Extended European Search Report for EP Application No. 20912344.7, dated on Feb. 23, 2023. [cited by applicant]