Tongue segmentation method based on dual encoding feature extraction path
FENG Xiaoyan
TIAN Qi
XU Yunfeng
CONG Jinyu
LIU Kunmeng
WANG Pingping
WEI Benzheng
Abstract：Aiming at the problems such as blurred tongue edge segmentation and small domain segmentation errors in tongue ima-ges,a segmentation method with dual encoding feature extraction paths was designed to obtain rich information features and assist tongue segmentation accurately.Firstly,a dual encoding feature extraction pathway was designed,in which the spatial information path preserved spatial information and generated high-resolution feature maps,and contextual information pathway enhanced the network's a-bility to extract multi-scale features.Then,a feature fusion module was adopted to merge the output features from spatial information paths and contextual information paths.Finally,a lightweight decoder module was adopted to reduce the number of network model pa-rameters and improve the computational efficiency of the model.The results showed that the precision,recall,F1 score,and mean in-tersection over union(MIoU)of the algorithm reached 98.82%,98.53%,98.60%,and 97.67%,respectively.The total parameter counts and floating-point operations per second(FLOPs)of the model were 7.54 M and 67.09 G.The results demonstrate that this algo-rithm effectively enhances the accuracy of tongue body segmentation,significantly improves the segmentation errors and edge fuzziness in small areas of the tongue body.This method can provide essential support for intelligent auxiliary analysis of traditional Chinese medi-cine tongue images.
Keywords：Tongue segmentationObjectification of tongue diagnosisDeep learningTransformerMulti-scale feature extraction
Publication Date：2024-04-28
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：6( 123-128 )