Surgical-DeSAM: decoupling SAM for instrument segmentation in robotic surgery

Download PDF
Open Webpage

Yuyang Sheng, Sophia Bano, Matthew J. Clarkson, Mobarakol Islam

Published: 01 Jan 2024, Last Modified: 06 Mar 2025Int. J. Comput. Assist. Radiol. Surg. 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: The recent segment anything model (SAM) has demonstrated impressive performance with point, text or bounding box prompts, in various applications. However, in safety-critical surgical tasks, prompting is not possible due to (1) the lack of per-frame prompts for supervised learning, (2) it is unrealistic to prompt frame-by-frame in a real-time tracking application, and (3) it is expensive to annotate prompts for offline applications.