CSpace  > 中国科学院计算技术研究所期刊论文  > 英文
Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis
Wei, Xiao-Yong1,2; Yang, Zhen-Qun3; Zhang, Xu-Lu1,2; Liao, Ga4; Sheng, Ai-Lin1,2; Zhou, S. Kevin5,6,7; Wu, Yongkang8; Du, Liang9,10
2021-07-01
发表期刊IEEE TRANSACTIONS ON MEDICAL IMAGING
ISSN0278-0062
卷号40期号:7页码:1898-1910
摘要Immunofixation Electrophoresis (IFE) analysis is of great importance to the diagnosis of Multiple Myeloma, which is among the top-9 cancer killers in the United States, but has rarely been studied in the context of deep learning. Two possible reasons are: 1) the recognition of IFE patterns is dependent on the co-location of bands that forms a binary relation, different from the unary relation (visual features to label) that deep learning is good at modeling; 2) deep classification models may perform with high accuracy for IFE recognition but is not able to provide firm evidence (where the co-location patterns are) for its predictions, rendering difficulty for technicians to validate the results. We propose to address these issues with collocative learning, in which a collocative tensor has been constructed to transform the binary relations into unary relations that are compatible with conventional deep networks, and a location-label-free method that utilizes the Grad-CAM saliency map for evidence backtracking has been proposed for accurate localization. In addition, we have proposed Coached Attention Gates that can regulate the inference of the learning to be more consistent with human logic and thus support the evidence backtracking. The experimental results show that the proposed method has obtained a performance gain over its base model ResNet18 by 741.30% in IoU and also outperformed popular deep networks of DenseNet, CBAM, and Inception-v3.
关键词Tensors Visualization Computational modeling Proteins Analytical models Logic gates Backtracking Immunofixation Electrophoresis deep collocative learning coached attention gates
DOI10.1109/TMI.2021.3068404
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[61872256] ; National Natural Science Foundation of China[81772275] ; Science and Technology Department of Sichuan Province[2020YFS0125]
WOS研究方向Computer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000668842500014
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
被引频次:11[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/17511
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Wu, Yongkang; Du, Liang
作者单位1.Sichuan Univ, Coll Comp Sci, Chengdu 610065, Peoples R China
2.Peng Cheng Lab, Ctr Artificial Intelligence, Shenzhen 518055, Peoples R China
3.Chinese Univ Hong Kong, Dept Biomed Engn, Hong Kong, Peoples R China
4.Sichuan Univ, West China Hosp Stomatol, Natl Clin Res Ctr Oral Dis, State Key Lab Oral Dis, Chengdu 610041, Peoples R China
5.Univ Sci & Technol China, Sch Biomed Engn, Med Imaging Robot & Analyt Comp Lab & Engn MIRACL, Suzhou 215123, Peoples R China
6.Univ Sci & Technol China, Suzhou Inst Adv Res, Suzhou 215123, Peoples R China
7.Chinese Acad Sci, CAS, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
8.Sichuan Univ, West China Hosp, Dept Lab Med & Outpatient, Chengdu 610041, Peoples R China
9.Sichuan Univ, West China Hosp, Med Device Regulatory Res & Evaluat Ctr, Chengdu 610041, Peoples R China
10.Sichuan Univ, West China Hosp, Chinese Evidence Based Med Ctr, Chengdu 610041, Peoples R China
推荐引用方式
GB/T 7714
Wei, Xiao-Yong,Yang, Zhen-Qun,Zhang, Xu-Lu,et al. Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2021,40(7):1898-1910.
APA Wei, Xiao-Yong.,Yang, Zhen-Qun.,Zhang, Xu-Lu.,Liao, Ga.,Sheng, Ai-Lin.,...&Du, Liang.(2021).Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis.IEEE TRANSACTIONS ON MEDICAL IMAGING,40(7),1898-1910.
MLA Wei, Xiao-Yong,et al."Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis".IEEE TRANSACTIONS ON MEDICAL IMAGING 40.7(2021):1898-1910.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Wei, Xiao-Yong]的文章
[Yang, Zhen-Qun]的文章
[Zhang, Xu-Lu]的文章
百度学术
百度学术中相似的文章
[Wei, Xiao-Yong]的文章
[Yang, Zhen-Qun]的文章
[Zhang, Xu-Lu]的文章
必应学术
必应学术中相似的文章
[Wei, Xiao-Yong]的文章
[Yang, Zhen-Qun]的文章
[Zhang, Xu-Lu]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。