Surgical instrument segmentation and classification in transcanal endoscopic ear surgery video using Segment Anything Model 2.

ABSTRACT:

Background

Accurate automatic recognition of surgical instruments is important for enhancing the safety and efficiency of transcanal endoscopic ear surgery (TEES). Segment Anything Model 2 (SAM 2) is a state-of-the-art artificial intelligence (AI) model featuring "zero-shot segmentation", which allows it to identify objects without extensive training data. The purpose of this study was to be the first to apply SAM 2 to TEES videos to evaluate its performance in segmenting and classifying surgical instruments.

Methods

From videos of three clinical TEES cases (tympanoplasty), we created a 684-frame evaluation video that simulated the sequential use of four types of surgical instruments: cupped forceps, pick, alligator forceps, and circular knife. SAM 2 was instructed to identi

SUBMITTER: Ueno R 

PROVIDER: S-EPMC12686742 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature