Deep learning-based surgical phase recognition in laparoscopic cholecystectomy.

ABSTRACT:

Backgrounds/aims

Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases.

Methods

One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. The

SUBMITTER: Yang HY 

PROVIDER: S-EPMC11599821 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature