Knowledge Commons of Institute of Automation,CAS
Dual Encoding U-Net for Retinal Vessel Segmentation | |
Bo,Wang1,2; Shuang,Qiu2; Huiguang,He1,2,3 | |
2019-10 | |
会议名称 | International Conference on Medical Image Computing and Computer-Assisted Intervention |
会议日期 | 2019-10-13 |
会议地点 | 中国深圳 |
摘要 | Retinal Vessel Segmentation is an essential step for the early diagnosis of eye-related diseases, such as diabetes and hypertension. Segmentation of blood vessels requires both sizeable receptive field and rich spatial information. In this paper, we propose a novel Dual Encoding U-Net (DEU-Net), which have two encoders: a spatial path with large kernel to preserve the spatial information and a context path with multiscale convolution block to capture more semantic information. On the top of the two paths, we introduce a feature fusion module to combine the different level of feature representation. Besides, we apply channel attention to select useful feature map in a skip connection. Furthermore, low-level and high-level prediction are combined in multiscale prediction module for a better accuracy. We evaluated this model on the digital retinal images for vessel extraction (DRIVE) dataset and the child heart and health study (CHASEDB1) dataset. Results show that the proposed DEU-Net model achieved the state-of-the-art retinal vessel segmentation accuracy on both datasets. |
收录类别 | EI |
七大方向——子方向分类 | 医学影像处理与分析 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44913 |
专题 | 脑图谱与类脑智能实验室_神经计算与脑机交互 |
通讯作者 | Huiguang,He |
作者单位 | 1.the School of Artificial Intelligence, University of Chinese Academy of Sciences 2.Research Center for Brain-inspired Intelligence and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 3.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Bo,Wang,Shuang,Qiu,Huiguang,He. Dual Encoding U-Net for Retinal Vessel Segmentation[C],2019. |
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