Computer-aided anatomy recognition in intrathoracic and -abdominal surgery: a systematic review.

ABSTRACT:

Background

Minimally invasive surgery is complex and associated with substantial learning curves. Computer-aided anatomy recognition, such as artificial intelligence-based algorithms, may improve anatomical orientation, prevent tissue injury, and improve learning curves. The study objective was to provide a comprehensive overview of current literature on the accuracy of anatomy recognition algorithms in intrathoracic and -abdominal surgery.

Methods

This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Pubmed, Embase, and IEEE Xplore were searched for original studies up until January 2022 on computer-aided anatomy recognition, without requiring intraoperative imaging or calibration equipment

SUBMITTER: den Boer RB 

PROVIDER: S-EPMC9652273 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature