Deep Learning based Segmentation of Optical Coherence Tomographic Images of Human Saphenous Varicose Vein

Abstract

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.