Deep-learning based segmentation model is proposed for Optical Coherence Tomography images of human varicose vein based on the U-Net model employing atrous convolution with residual blocks, which gives an accuracy of 0.9932.

翻译：提议以深层学习为基础的分离模型,用于根据U-Net模型,使用与残余区块发生突变的U-Net模型,制作人类变形血管的光学一致性成像摄影图象,精确度为0.9932。</s>