BiMNet: A Multimodal Data Fusion Network for continuous circular capsulorhexis Action Segmentation

doi:10.1016/j.eswa.2023.121885

	BiMNet: A Multimodal Data Fusion Network for continuous circular capsulorhexis Action Segmentation
	Bian, Gui-Bin1,2 ; Zheng, Jia-Ying 1,2; Li, Zhen2 ; Wang, Jie1,2 ; Fu, Pan 1,2; Xin, Chen 3; da Silva, Daniel Santos 4; Wu, Wan-Qing 5; De Albuquerque, Victor Hugo C.4
发表期刊	EXPERT SYSTEMS WITH APPLICATIONS
ISSN	0957-4174
	2024-03-15
卷号	238 页码:10
通讯作者	Bian, Gui-Bin(guibin.bian@ia.ac.cn)
摘要	Completing continuous circular capsulorhexis (CCC) requires the operator to perform fine operations, which is difficult to do accurately when continuous fine actions are out of balance in the classification of CCC procedures. Multimodal deep learning can improve the classifier's performance, but the recognition accuracy of inferior classes is difficult to improve. To solve these problems, a bidirect-gate recurrent unit (Bi-GRU)-attention-based multimodal, multi-timescale data fusion network (BiMNet) is proposed, which contains a data extraction module called a skip-concatenate gate recurrent unit (SC-GRU), a bimodal data fusion attention computation, and a decoder module. The combination of these modules can fully extract the features of different temporal scales in multimodal action data and fuse them effectively. The model is validated using the ophthalmologist CCC multimodal maneuver dataset, which was collected by the data collection platform constructed in this research, achieving an accuracy of 0.9124 +/- 0.0125 in continuous action sequence segmentation and improving the F1-score of minority class recognition to over 80%, making it more effective than baseline algorithms.
关键词	Cataract surgery Continuous circumferential capsulotomy Continuous action segmentation Multimodal data fusion Imbalanced data
DOI	10.1016/j.eswa.2023.121885
收录类别	SCI
语种	英语
资助项目	National Natural Science Foun-dation of China[62027813] ; National Natural Science Foun-dation of China[U20A20196] ; National Key Re-search and Development Program of China[2022YFB4702900] ; Beijing Science Fund for Distinguished Young Scholars, China[JQ21016] ; Excellent member of CAS Youth Innovation Promotion Association, China[Y2022054]
项目资助者	National Natural Science Foun-dation of China ; National Key Re-search and Development Program of China ; Beijing Science Fund for Distinguished Young Scholars, China ; Excellent member of CAS Youth Innovation Promotion Association, China
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:001088900900001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/54293
专题	多模态人工智能系统全国重点实验室多模态人工智能系统全国重点实验室_智能机器人系统研究
通讯作者	Bian, Gui-Bin
作者单位	1.Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100096, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Capital Med Univ, Beijing Tongren Hosp, Ophthalmol Dept, Beijing 100005, Peoples R China 4.Univ Fed Ceara, Dept Teleinformat Engn, BR-60811905 Fortaleza, CE, Brazil 5.Sun Yat Sen Univ, Sch Biomed Engn, Guangzhou 510275, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Bian, Gui-Bin,Zheng, Jia-Ying,Li, Zhen,et al. BiMNet: A Multimodal Data Fusion Network for continuous circular capsulorhexis Action Segmentation[J]. EXPERT SYSTEMS WITH APPLICATIONS,2024,238:10.
APA	Bian, Gui-Bin.,Zheng, Jia-Ying.,Li, Zhen.,Wang, Jie.,Fu, Pan.,...&De Albuquerque, Victor Hugo C..(2024).BiMNet: A Multimodal Data Fusion Network for continuous circular capsulorhexis Action Segmentation.EXPERT SYSTEMS WITH APPLICATIONS,238,10.
MLA	Bian, Gui-Bin,et al."BiMNet: A Multimodal Data Fusion Network for continuous circular capsulorhexis Action Segmentation".EXPERT SYSTEMS WITH APPLICATIONS 238(2024):10.