Automated Tongue Segmentation in Chinese Medicine Based on Deep Learning

Abstract

During the process of tongue diagnosis automation, the segmentation of tongue body from the original image is an important part. Tongue body is a target with irregular edge, and the color of local area is similar to that of lips, so it is difficult to achieve accurate segmentation with traditional segmentation methods. In this paper, we present a tongue image segmentation method based on deep learning. We first apply semantic segmentation to tongue segmentation that use fully convolutional networks to automatically segment tongue body based on preserving tongue shape semantic information. Moreover, we try to combine it with traditional algorithm to optimize the results. The experimental results show that the semantic segmentation method based on neural network is superior to the traditional algorithm in accuracy and efficiency. In addition, comparing with traditional algorithms, the method does not require manual label, which greatly reduces the workload.