An Automatic Glioma Segmentation System Based on A Separable Attention U-Net (SAUNet)
文献类型：会议论文
| 作者 | Zhang, Zhenyu2; Gao, Shouwei2; Huang Z(黄钲)1 |
| 出版日期 | 2020 |
| 会议日期 | October 16-18, 2020 |
| 会议地点 | Virtual, Online, China |
| 关键词 | Glioma segmentation Separable attention U-Net |
| 页码 | 95-101 |
| 英文摘要 | With the complicated structure of brains, glioma segmentation is a challenging task. To precisely segment gliomas, U-Net structure is adopted by most current methods. However, the computation complexity of U-Net based method is large. Therefore, a separable attention U-Net, which can reduce the computation complexity without decreasing the performance, is proposed in this paper. Firstly, data augmentation techniques are implemented to enlarge the database and thus avoid over-fitting; Moreover, the separable attention U-Net is constructed for glioma segmentation. The experimental results indicate that the dice similarity coefficient of the proposed separable attention U-Net can reach 0.879 with the parameter number of 4.29 M, which indicates that the proposed glioma segmentation method is of application significance. A single column document that allows authors to type theircontent into the pre-existing set of paragraph formatting styles applied to the sample placeholder text here. Throughout the document you will find further instructions on how to format your text. |
| 产权排序 | 2 |
| 会议录 | Proceedings of 2020 9th International Conference on Bioinformatics and Biomedical Science, ICBBS 2020
 |
| 会议录出版者 | ACM |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-4503-8865-8 |
| 源URL | [http://ir.sia.cn/handle/173321/28293]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Zhang, Zhenyu |
| 作者单位 | 1.Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China 2.School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China |
| 推荐引用方式 GB/T 7714 | Zhang, Zhenyu,Gao, Shouwei,Huang Z. An Automatic Glioma Segmentation System Based on A Separable Attention U-Net (SAUNet)[C]. 见:. Virtual, Online, China. October 16-18, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
浏览0
下载0
收藏0
其他版本
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。