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VoxSeP: semi-positive voxels assist self-supervised 3D medical segmentation

文献类型：期刊论文

作者Yang, Zijie4,5; Xie, Lingxi1; Zhou, Wei1; Huo, Xinyue6; Wei, Longhui1; Lu, Jian3; Tian, Qi1; Tang, Sheng2,4,5
刊名MULTIMEDIA SYSTEMS
出版日期2022-07-23
页码16
关键词3D medical image segmentation Contrastive learning Self-supervised learning Unsupervised learning
ISSN号0942-4962
DOI10.1007/s00530-022-00977-9
英文摘要Medical image segmentation enjoys the advantage of understanding 3D contexts, but 3D networks are prone to over-fitting due to the limited amount of annotated data. This paper investigates self-supervised pre-training, i.e., making use of unlabeled medical data to initialize 3D segmentation networks. We build our system upon contrastive learning, where the dependence on positive and negative samples obstructs it from satisfying performance on medical image datasets with fewer samples. To alleviate this issue, we present a novel proxy task that takes advantage of the property of human body similarity in medical scans, and defines the sub-volumes from the same position of different cases as Semi-Positive samples. Pre-trained on a mixed dataset containing 1254 CT volumes, the proposed approach, VoxSeP, transfers well to 4 downstream datasets with 2 different backbone networks. On both fully supervised and semi-supervised fine-tuning, VoxSeP achieves favorable averaged improvements (2% and 4%), which surpass several state-of-the-art counterparts.
资助项目National Natural Science Foundation of China[61871004] ; Project of Chinese Academy of Sciences[E141020]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000829128600001
出版者SPRINGER
源URL[http://119.78.100.204/handle/2XEOYT63/19480]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Tang, Sheng
作者单位1.Huawei Cloud, Beijing, Peoples R China
2.Zhejiang Lab, Res Inst Intelligent Comp, Hangzhou, Peoples R China
3.Peking Univ Third Hosp, Dept Urol, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
6.Univ Sci & Technol China, Hefei, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Zijie,Xie, Lingxi,Zhou, Wei,et al. VoxSeP: semi-positive voxels assist self-supervised 3D medical segmentation[J]. MULTIMEDIA SYSTEMS,2022:16.
APA Yang, Zijie.,Xie, Lingxi.,Zhou, Wei.,Huo, Xinyue.,Wei, Longhui.,...&Tang, Sheng.(2022).VoxSeP: semi-positive voxels assist self-supervised 3D medical segmentation.MULTIMEDIA SYSTEMS,16.
MLA Yang, Zijie,et al."VoxSeP: semi-positive voxels assist self-supervised 3D medical segmentation".MULTIMEDIA SYSTEMS (2022):16.

入库方式： OAI收割

来源：计算技术研究所

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