AGNet: Attention-guided network for surgical tool presence detection

Xiaowei Hu, Lequan Yu, Hao Chen, Jing Qin, Pheng Ann Heng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

21 Citations (Scopus)

Abstract

We propose a novel approach to automatically recognize the presence of surgical tools in surgical videos, which is quite challenging due to the large variation and partially appearance of surgical tools, the complicated surgical scenes, and the co-occurrence of some tools in the same frame. Inspired by human visual attention mechanism, which first orients and selects some important visual cues and then carefully analyzes these focuses of attention, we propose to first leverage a global prediction network to obtain a set of visual attention maps and a global prediction for each tool, and then harness a local prediction network to predict the presence of tools based on these attention maps. We apply a gate function to obtain the final prediction results by balancing the global and the local predictions. The proposed attention-guided network (AGNet) achieves state-of-the-art performance on m2cai16-tool dataset and surpasses the winner in 2016 by a significant margin.
Original languageEnglish
Title of host publicationDeep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - 3rd International Workshop, DLMIA 2017 and 7th International Workshop, ML-CDS 2017 Held in Conjunction with MICCAI 2017, Proceedings
PublisherSpringer Verlag
Pages186-194
Number of pages9
ISBN (Print)9783319675572
DOIs
Publication statusPublished - 1 Jan 2017
Event3rd International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017 and 7th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 14 Sept 201714 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10553 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017 and 7th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period14/09/1714/09/17

Keywords

  • Attention-guided network
  • Cholecystectomy
  • Deep learning
  • Laparoscopic videos
  • Surgical tool recognition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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