液晶与显示2024，Vol.39Issue(8)：1014-1023,10.DOI:10.37188/CJLCD.2023-0308
基于双模型互学习的半监督中医舌诊图像分割方法
Semi-supervised tongue image segmentation method for traditional chinese medicine based on mutual learning with dual models
摘要
Abstract
Accurate tongue image segmentation is a crucial prerequisite for objective analysis in tongue diagnosis in traditional Chinese medicine(TCM).At present,the widely-used full-supervised segmentation methods require a large number of pixel-level annotated samples for training,and the single-model-based semi-supervised segmentation methods lack the ability to self-correct the learned error knowledge.To address this issue,a novel semi-supervised tongue image segmentation method based on mutual learning with dual models is proposed.Firstly,model A and B undergo supervised training on the labeled datasets.Subsequently,model A and B enter the mutual learning phase,utilizing a designed mutual learning loss function,in which different weights are assigned based on the disagreement between predictions of the two models on the unlabeled data.Model A generates the pseudo-labels for the unlabeled dataset,and model B fine-tunes on both the labeled dataset and the pseudo-labeled dataset.Then,model B generates the pseudo-labels for the unlabeled dataset,and model A fine-tunes in the same manner.After the dual-model fine-tuning process,the model with better performance is selected as the final tongue image segmentation model.Experimental results show that with labeled data proportions of 1/100,1/50,1/25,and 1/8,the mean intersection over union(mIoU)achieved by the proposed method is 96.67%,97.92%,98.52%,and 98.85%,respectively,outperforming other typical semi-supervised methods compared.The proposed method achieves high precision in tongue image segmentation with only a small number of labeled data,laying a solid foundation for subsequent applications in TCM such as tongue color,tongue shape and other tongue image analysis,which can promote the digitization of TCM diagnosis and treatment.关键词
半监督/互学习/舌体图像分割/损失函数/中医数字化Key words
semi-supervised/mutual learning/tongue image segmentation/loss function/digitization of TCM分类
信息技术与安全科学引用本文复制引用
李方旭,徐望明,徐雪,贾云..基于双模型互学习的半监督中医舌诊图像分割方法[J].液晶与显示,2024,39(8):1014-1023,10.基金项目
国家自然科学基金(No.51805386) （No.51805386）
国家重点研发计划(No.3502300,No.3502302)Supported by National Natural Science Foundation of China(No.51805386) （No.3502300,No.3502302）
National Key R&D Program of China(No.3502300,No.3502302) （No.3502300,No.3502302）
