机译:通过融合上下文感知的混合特征在视网膜图像中进行区分性血管分割
Department of Computer and Information Science, Temple University, Philadelphia, PA 19122, USA;
Department of Computer and Information Science, Temple University, Philadelphia, PA 19122, USA;
School of Information and Control Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China;
Electrical and Computer Engineering Department, Temple University, Philadelphia, PA 19122, USA;
Department of Computer and Information Science, Temple University, Philadelphia, PA 19122, USA, Computer Engineering and Informatics Department, University of Patras, 26500 Patras, Greece;
Department of Computer and Information Science, Temple University, Philadelphia, PA 19122, USA;
Vessel segmentation; Random forest; Stroke width transform; Weber's local descriptors;
机译:通过鉴别特征学习改善视网膜血管分割的致密条件随机场
机译:基于灰度和不变矩特征的神经网络(Nn)方案对视网膜图像中的血管进行分割
机译:一种改进的基于高级特征的视网膜血管病理图像分割方法
机译:用于改进薄型视网膜血管分割的多判别器生成对抗网络
机译:张量表决法在眼底图像中分割和表征小视网膜血管
机译:视网膜血管分割的杂交无监督方法
机译:视网膜图像中血管分割的混合学习