HFCAS OpenIR
MSU-Net: Multi-Scale U-Net for 2D Medical Image Segmentation
Su, Run1,2; Zhang, Deyun3; Liu, Jinhuai1,2; Cheng, Chuandong4,5,6
2021-02-11
Source PublicationFRONTIERS IN GENETICS
Corresponding AuthorLiu, Jinhuai(jhliu@iim.ac.cn)
AbstractAiming at the limitation of the convolution kernel with a fixed receptive field and unknown prior to optimal network width in U-Net, multi-scale U-Net (MSU-Net) is proposed by us for medical image segmentation. First, multiple convolution sequence is used to extract more semantic features from the images. Second, the convolution kernel with different receptive fields is used to make features more diverse. The problem of unknown network width is alleviated by efficient integration of convolution kernel with different receptive fields. In addition, the multi-scale block is extended to other variants of the original U-Net to verify its universality. Five different medical image segmentation datasets are used to evaluate MSU-Net. A variety of imaging modalities are included in these datasets, such as electron microscopy, dermoscope, ultrasound, etc. Intersection over Union (IoU) of MSU-Net on each dataset are 0.771, 0.867, 0.708, 0.900, and 0.702, respectively. Experimental results show that MSU-Net achieves the best performance on different datasets. Our implementation is available at https://github.com/CN-zdy/MSU_Net..
Keywordmulti-scale block U-net medical image segmentation convolution kernel receptive field
DOI10.3389/fgene.2021.639930
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[62033002] ; Science and Technology Project grant from Anhui Province[1508085QHl84] ; Science and Technology Project grant from Anhui Province[201904a07020098] ; Fundamental Research Fund for the Central Universities[WK 9110000032]
Funding OrganizationNational Natural Science Foundation of China ; Science and Technology Project grant from Anhui Province ; Fundamental Research Fund for the Central Universities
WOS Research AreaGenetics & Heredity
WOS SubjectGenetics & Heredity
WOS IDWOS:000621359800001
PublisherFRONTIERS MEDIA SA
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.hfcas.ac.cn:8080/handle/334002/120162
Collection中国科学院合肥物质科学研究院
Corresponding AuthorLiu, Jinhuai
Affiliation1.Chinese Acad Sci, Hefei Inst Phys Sci, Inst Intelligent Machines, Hefei, Peoples R China
2.Univ Sci & Technol China, Grad Sch, Sci Isl Branch, Hefei, Peoples R China
3.Anhui Agr Univ, Sch Engn, Hefei, Peoples R China
4.Univ Sci & Technol China USTC, Affiliated Hosp 1, Dept Neurosurg, Hefei, Peoples R China
5.Univ Sci & Technol China, Div Life Sci & Med, Hefei, Peoples R China
6.Anhui Prov Key Lab Brain Funct & Brain Dis, Hefei, Peoples R China
Recommended Citation
GB/T 7714
Su, Run,Zhang, Deyun,Liu, Jinhuai,et al. MSU-Net: Multi-Scale U-Net for 2D Medical Image Segmentation[J]. FRONTIERS IN GENETICS,2021,12.
APA Su, Run,Zhang, Deyun,Liu, Jinhuai,&Cheng, Chuandong.(2021).MSU-Net: Multi-Scale U-Net for 2D Medical Image Segmentation.FRONTIERS IN GENETICS,12.
MLA Su, Run,et al."MSU-Net: Multi-Scale U-Net for 2D Medical Image Segmentation".FRONTIERS IN GENETICS 12(2021).
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