MSU-Net: A multi-scale U-Net for retinal vessel segmentation
文献类型：会议论文
| 作者 | Shi, Zhengjin1; Wang, Tianyu1 ; Xie, Feng1; Huang Z(黄钲)2; Zheng, Xinyu1; Zhang, Wenjiao1
|
| 出版日期 | 2020 |
| 会议日期 | September 11-13, 2020 |
| 会议地点 | Beijing, China |
| 关键词 | Deep learning Retinal vessel segmentation Image processing Fundus image Convolutional neural network |
| 页码 | 177-181 |
| 英文摘要 | Retinal vessel segmentation is widely used in the diagnosis of eye diseases, and the effect of segmentation plays a crucial role in whether doctors can correctly diagnose diseases. To further improve the accuracy of the automatic segmentation method, a network structure named Multi-Scale U-Net (MSU-Net) based on deep learning is proposed in this paper. The network combines Atrous Spatial Pyramid Pooling (ASPP) module to extract multi-scale information, making the U-Net more suitable for segmentation of complex and changeable vessel structures. We evaluate the network on two public databases, DRIVE and STARE. The Accuracy (ACC), Sensitivity (SEN), Specificity (SPE) and Dice coefficient on the DRIVE database are 0.9667, 0.8159, 0.9805 and 0.8059, respectively. These indicators are respectively 0.9732, 0.8272, 0.9866 and 0.8400 on the STARE database. Experiments show that the network has excellent segmentation results, and has state-of-the-art performance indicators on the STARE database, which fully proves the outstanding performance of the network. © 2020 ACM. |
| 产权排序 | 2 |
| 会议录 | Proceedings of the 2020 International Symposium on Artificial Intelligence in Medical Sciences, ISAIMS 2020
 |
| 会议录出版者 | ACM |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-4503-8860-3 |
| 源URL | [http://ir.sia.cn/handle/173321/28350]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Wang, Tianyu |
| 作者单位 | 1.School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Shi, Zhengjin,Wang, Tianyu,Xie, Feng,et al. MSU-Net: A multi-scale U-Net for retinal vessel segmentation[C]. 见:. Beijing, China. September 11-13, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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