Knowledge Management System of Hefei Institute of Physical Science，CAS
| Multimodal Glioma Image Segmentation Using Dual Encoder Structure and Channel Spatial Attention Block | |
Su, Run1,2; Liu, Jinhuai1,2 ; Zhang, Deyun3; Cheng, Chuandong4,5,6; Ye, Mingquan7
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| 2020-10-28 | |
| Source Publication | FRONTIERS IN NEUROSCIENCE
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| Corresponding Author | Liu, Jinhuai(jhliu@iim.ac.cn) |
| Abstract | Multimodal medical images provide significant amounts of complementary semantic information. Therefore, multimodal medical imaging has been widely used in the segmentation of gliomas through computational neural networks. However, inputting images from different sources directly to the network does not achieve the best segmentation effect. This paper describes a convolutional neural network called F-S-Net that fuses the information from multimodal medical images and uses the semantic information contained within these images for glioma segmentation. The architecture of F-S-Net is formed by cascading two sub-networks. The first sub-network projects the multimodal medical images into the same semantic space, which ensures they have the same semantic metric. The second sub-network uses a dual encoder structure (DES) and a channel spatial attention block (CSAB) to extract more detailed information and focus on the lesion area. DES and CSAB are integrated into U-Net architectures. A multimodal glioma dataset collected by Yijishan Hospital of Wannan Medical College is used to train and evaluate the network. F-S-Net is found to achieve a dice coefficient of 0.9052 and Jaccard similarity of 0.8280, outperforming several previous segmentation methods. |
| Keyword | medical image fusion glioma segmentation fully convolutional neural networks DES CSAB F-S-Net |
| DOI | 10.3389/fnins.2020.586197 |
| WOS Keyword | DEEP |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 Organization | Science and Technology Project grant from Anhui Province ; Fundamental Research Fund for the Central Universities |
| WOS Research Area | Neurosciences & Neurology |
| WOS Subject | Neurosciences |
| WOS ID | WOS:000588015400001 |
| Publisher | FRONTIERS MEDIA SA |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.hfcas.ac.cn:8080/handle/334002/105071 |
| Collection | 中国科学院合肥物质科学研究院 |
| Corresponding Author | Liu, Jinhuai |
| Affiliation | 1.Chinese Acad Sci, Hefei Inst Phys Sci, Inst Intelligent Machines, Hefei, Peoples R China 2.Univ Sci & Technol China, Sci Isl Branch, Grad Sch, Hefei, Peoples R China 3.Anhui Agr Univ, Sch Engn, Hefei, Peoples R China 4.Univ Sci & Technol China, 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 7.Wannan Med Coll, Sch Med Informat, Wuhu, Peoples R China |
| Recommended Citation GB/T 7714 | Su, Run,Liu, Jinhuai,Zhang, Deyun,et al. Multimodal Glioma Image Segmentation Using Dual Encoder Structure and Channel Spatial Attention Block[J]. FRONTIERS IN NEUROSCIENCE,2020,14. |
| APA | Su, Run,Liu, Jinhuai,Zhang, Deyun,Cheng, Chuandong,&Ye, Mingquan.(2020).Multimodal Glioma Image Segmentation Using Dual Encoder Structure and Channel Spatial Attention Block.FRONTIERS IN NEUROSCIENCE,14. |
| MLA | Su, Run,et al."Multimodal Glioma Image Segmentation Using Dual Encoder Structure and Channel Spatial Attention Block".FRONTIERS IN NEUROSCIENCE 14(2020). |
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