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:
Apr. 28, 2026

Filed:

Dec. 08, 2022
Applicant:

Verb Surgical Inc., Santa Clara, CA (US);

Inventors:

Mona Fathollahi Ghezelghieh, Sunnyvale, CA (US);

Jocelyn Barker, San Jose, CA (US);

Assignee:

Auris Health, Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/246 (2017.01); A61B 34/20 (2016.01); G06V 10/26 (2022.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06T 7/246 (2017.01); A61B 34/20 (2016.02); G06V 10/26 (2022.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); A61B 2034/2065 (2016.02); G06T 2207/10016 (2013.01); G06T 2207/10068 (2013.01); G06V 2201/034 (2022.01);
Abstract

Disclosed are various systems and techniques for tracking surgical tools in a surgical video. In one aspect, the system begins by receiving one or more established tracks for one or more previously-detected surgical tools in the surgical video. The system then processes a current frame of the surgical video to detect one or more objects using a first deep-learning model. Next, for each detected object in the one or more detected objects, the system further performs the flowing steps to assign the detected object to a right track: (1) computing a semantic similarity between the detected object and each of the one or more established tracks; (2) computing a spatial similarity between the detected object and the latest predicted location for each of the one or more established tracks; and (3) attempting to assign the detected object to one of the one or more established tracks based on the computed semantic similarity and the spatial similarity metric.


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