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MSDE-Net: A Multi-Scale Dual-Encoding Network for Surgical Instrument Segmentation

文献类型：期刊论文

作者Yang, Lei1; Gu, Yuge1; Bian, Guibin1,2; Liu, Yanhong1
刊名IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
出版日期2024-07-01
卷号28期号:7页码:4072-4083
关键词Surgical instrument segmentation transformer dual-branch encoder feature fusion
ISSN号2168-2194
DOI10.1109/JBHI.2023.3344716
通讯作者Bian, Guibin(guibin.bian@ia.ac.cn) ; Liu, Yanhong(liuyh@zzu.edu.cn)
英文摘要Minimally invasive surgery, which relies on surgical robots and microscopes, demands precise image segmentation to ensure safe and efficient procedures. Nevertheless, achieving accurate segmentation of surgical instruments remains challenging due to the complexity of the surgical environment. To tackle this issue, this paper introduces a novel multiscale dual-encoding segmentation network, termed MSDE-Net, designed to automatically and precisely segment surgical instruments. The proposed MSDE-Net leverages a dual-branch encoder comprising a convolutional neural network (CNN) branch and a transformer branch to effectively extract both local and global features. Moreover, an attention fusion block (AFB) is introduced to ensure effective information complementarity between the dual-branch encoding paths. Additionally, a multilayer context fusion block (MCF) is proposed to enhance the network's capacity to simultaneously extract global and local features. Finally, to extend the scope of global feature information under larger receptive fields, a multi-receptive field fusion (MRF) block is incorporated. Through comprehensive experimental evaluations on two publicly available datasets for surgical instrument segmentation, the proposed MSDE-Net demonstrates superior performance compared to existing methods.
WOS关键词IMAGE SEGMENTATION ; SURGERY ; COLOR ; ROBOT
资助项目National Key Research & Development Project of China[2020YFB1313701] ; National Natural Science Foundation of China[62003309]
WOS研究方向Computer Science ; Mathematical & Computational Biology ; Medical Informatics
语种英语
WOS记录号WOS:001263692800013
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research & Development Project of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/59219]  
专题智能机器人系统研究
通讯作者Bian, Guibin; Liu, Yanhong
作者单位1.Zhengzhou Univ, Sch Elect & Informat Engn, Zhengzhou 450001, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Lei,Gu, Yuge,Bian, Guibin,et al. MSDE-Net: A Multi-Scale Dual-Encoding Network for Surgical Instrument Segmentation[J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,2024,28(7):4072-4083.
APA Yang, Lei,Gu, Yuge,Bian, Guibin,&Liu, Yanhong.(2024).MSDE-Net: A Multi-Scale Dual-Encoding Network for Surgical Instrument Segmentation.IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,28(7),4072-4083.
MLA Yang, Lei,et al."MSDE-Net: A Multi-Scale Dual-Encoding Network for Surgical Instrument Segmentation".IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 28.7(2024):4072-4083.

入库方式： OAI收割

来源：自动化研究所

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