SegmentOR: Obtaining Efficient Operating Room Semantics Through Temporal Propagation

Lennart Bastian, Daniel Derkacz-Bogner, Tony D. Wang, Benjamin Busam, Nassir Navab

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

Abstract

The digitization of surgical operating rooms (OR) has gained significant traction in the scientific and medical communities. However, existing deep-learning methods for operating room recognition tasks still require substantial quantities of annotated data. In this paper, we introduce a method for weakly-supervised semantic segmentation for surgical operating rooms. Our method operates directly on 4D point cloud sequences from multiple ceiling-mounted RGB-D sensors and requires less than 0.01% of annotated data. This is achieved by incorporating a self-supervised temporal prior, enforcing semantic consistency in 4D point cloud video recordings. We show how refining these priors with learned semantic features can increase segmentation mIoU to 10 % above existing works, achieving higher segmentation scores than baselines that use four times the number of labels. Furthermore, the 3D semantic predictions from our method can be projected back into 2D images; we establish that these 2D predictions can be used to improve the performance of existing surgical phase recognition methods. Our method shows promise in automating 3D OR segmentation with a 20 times lower annotation cost than existing methods, demonstrating the potential to improve surgical scene understanding systems.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings
EditorsHayit Greenspan, Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor
PublisherSpringer Science and Business Media Deutschland GmbH
Pages57-67
Number of pages11
ISBN (Print)9783031439957
DOIs
StatePublished - 2023
Event26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023 - Vancouver, Canada
Duration: 8 Oct 202312 Oct 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14228 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023
Country/TerritoryCanada
CityVancouver
Period8/10/2312/10/23

Keywords

  • Context-aware Systems
  • Surgical Data Science
  • Surgical Phase Recognition
  • Surgical Scene Understanding

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