Artificial intelligence-integrated video analysis of vessel area changes and instrument motion for microsurgical skill assessment.

ABSTRACT: Mastering microsurgical skills is essential for neurosurgical trainees. Video-based analysis of target tissue changes and surgical instrument motion provides an objective, quantitative method for assessing microsurgical proficiency, potentially enhancing training and patient safety. This study evaluates the effectiveness of an artificial intelligence (AI)-based video analysis model in assessing microsurgical performance and examines the correlation between AI-derived parameters and specific surgical skill components. A dual AI framework was developed, integrating a semantic segmentation model for artificial blood vessel analysis with an instrument tip-tracking algorithm. These models quantified dynamic vessel area fluctuation, tissue deformation error count, instrument path distance, and n

SUBMITTER: Sugiyama T 

PROVIDER: S-EPMC12314103 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature