The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 27, 2025

Filed:

Apr. 27, 2021
Applicant:

Given Imaging Ltd., Yoqneam, IL;

Inventors:

Dorit Baras, Haifa, IL;

Eyal Dekel, Haifa, IL;

Eva Niv, Hadera, IL;

Assignee:

Given Imaging LTD., Yoqneam, IL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 1/00 (2006.01); A61B 1/04 (2006.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06V 10/25 (2022.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 30/148 (2022.01);
U.S. Cl.
CPC ...
G06T 7/11 (2017.01); A61B 1/000094 (2022.02); A61B 1/000095 (2022.02); A61B 1/000096 (2022.02); A61B 1/041 (2013.01); G06T 7/0012 (2013.01); G06T 7/97 (2017.01); G06V 10/25 (2022.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 2207/10068 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30028 (2013.01); G06T 2207/30092 (2013.01); G06V 30/153 (2022.01); G06V 2201/031 (2022.01);
Abstract

In accordance with aspects of the present disclosure, a system includes at least one processor and at least one memory storing instructions which, when executed by the processor(s), cause the system to access images of a portion of a gastrointestinal tract (GIT) captured by a capsule endoscopy device; for each of the images, provide, by a deep learning neural network, scores for classifying the image to each of consecutive segments of the GIT; classify each image of a subset of the images, whose scores satisfy a confidence criterion, to one of the consecutive segments of the GIT; refine the classifications of the images in the subset by processing a signal over time corresponding to the classifications of the images in the subset; and estimate, among the images in the subset, a transition () between two adjacent segments of the GIT based on the refined classifications of the images in the subset.


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