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Anatomy-aware Assessment of Critical View of Safety with Spatial Relation Prior

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Critical View of Safety (CVS) is a set of widely accepted conditions that must be met during laparoscopic cholecystectomy (LC) surgeries, and it has been an important validation method for the prevention of bile duct injuries (BDIs). Recent methods explored using object detection and graph construction to facilitate downstream CVS classification, but given the intrinsic spatial relations between anatomical structures in an LC scene, such prior information has yet to be utilized. In this paper, we propose incorporating prior knowledge about spatial relations among anatomical structures to improve the assessment of CVS. We evaluated our method on the publicly available Endoscapes dataset, and achieved 1 ∼ 7% improvement on the baseline model in individual CVS conditions and over 9% in overall CVS classification.

Original languageEnglish
Title of host publication2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2025 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331586188
DOIs
StatePublished - 2025
Event47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2025 - Copenhagen, Denmark
Duration: Jul 14 2025Jul 18 2025

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2025
Country/TerritoryDenmark
CityCopenhagen
Period07/14/2507/18/25

Keywords

  • Critical View of Safety
  • Knowledge Graph
  • Laparoscopic Cholecystectomy
  • Object Detection

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