Tongue Semantic Segmentation Based on Fully Convolutional Neural Network

It is difficult to accurately segment the tongue due to the blurred contours and the similar colors of the surrounding tissue. This paper presents a semantic segmentation method for tongue body based on fully convolutional neural network. First, the convolutional and pooling layers are used to map the tongue image from the pixel domain to the feature domain. Then, the deconvolutional layer is used to restore the shrinking feature image to the original size. Finally, the Softmax classifier is trained to classify each point of the image in order to achieve segmentation. Experimental results show that the method proposed in this paper can get better segmentation results, laying a solid foundation for tongue analysis and dialectical diagnosis.