A Computer Vision Platform to Automatically Locate Critical Events in Surgical Videos

202186 citationsJournal Article

Authors

Pietro Mascagni · Agostino Gemelli University Polyclinic

Deepak Alapatt · Centre National de la Recherche Scientifique

Takeshi Urade · Institut de Chirurgie Guidée par l'Image

Armine Vardazaryan · Université de Strasbourg

Didier Mutter · Institut de Chirurgie Guidée par l'Image

Jacques Marescaux · Institut de Recherche contre les Cancers de l’Appareil Digestif

Guido Costamagna

Abstract

Deep learning models for workflow analysis can be used to reliably locate critical events in surgical videos and document CVS in LC. Further studies are needed to assess the clinical impact of surgical data science solutions for safer laparoscopic cholecystectomy.

Topics & Keywords

Surgical Simulation and Training Cardiac, Anesthesia and Surgical Outcomes Medical Malpractice and Liability Issues

Publication Details

Published in: Annals of Surgery

Volume 274, Issue 1, pp. e93-e95

DOI: 10.1097/sla.0000000000004736

Field-Weighted Citation Impact: 13.17

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A Computer Vision Platform to Automatically Locate Critical Events in Surgical Videos

Authors

Abstract

Topics & Keywords

Publication Details