Chinese Journal of Liquid Crystals and Displays, Volume. 39, Issue 8, 1014(2024)
Semi-supervised tongue image segmentation method for traditional chinese medicine based on mutual learning with dual models
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.
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Fangxu LI, Wangming XU, Xue XU, Yun JIA. Semi-supervised tongue image segmentation method for traditional chinese medicine based on mutual learning with dual models[J]. Chinese Journal of Liquid Crystals and Displays, 2024, 39(8): 1014
Category: Image Segmentation
Received: Sep. 22, 2023
Accepted: --
Published Online: Sep. 27, 2024
The Author Email: Yun JIA (jiayun@cug.edu.cn)