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Visual Modalities Based Multimodal Fusion for Surgical Phase Recognition

Authors
 Bogyu Park  ;  Hyeongyu Chi  ;  Bokyung Park  ;  Jiwon Lee  ;  Sunghyun Park  ;  Woo Jin Hyung  ;  Min-Kook Choi 
Citation
 Lecture Notes in Computer Science, Vol.13594 LNCS : 11-23, 2022-10 
Journal Title
Lecture Notes in Computer Science
ISSN
 0302-9743 
Issue Date
2022-10
Keywords
Surgical workflow ; Surgical phase recognition ; Multimodal learning ; Visual kinematics-based index
Abstract
We propose visual modalities-based multimodal fusion for surgical phase recognition to overcome the limitation of the diversity of information such as the presence of tools. Through the proposed methods, we extracted a visual kinematics-based index related to the usage of tools such as movement and the relation between tools in surgery. In addition, we improved recognition performance using the effective fusion method which is fusing CNN-based visual feature and visual kinematics-based index. The visual kinematics-based index is helpful for understanding the surgical procedure as the information related to the interaction between tools. Furthermore, these indices can be extracted in any environment unlike kinematics in robotic surgery. The proposed methodology was applied to two multimodal datasets to verify that it can help to improve recognition performance in clinical environments.
Full Text
https://link.springer.com/chapter/10.1007/978-3-031-18814-5_2
DOI
10.1007/978-3-031-18814-5_2
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
Yonsei Authors
Park, Sung Hyun(박성현)
Hyung, Woo Jin(형우진) ORCID logo https://orcid.org/0000-0002-8593-9214
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/193875
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