ArticleInternational journal of computer assisted radiology and surgery2020
Tongue color clustering and visual application based on 2D information.
Article in International journal of computer assisted radiology and surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 18 citations in OpenAlex.
- Temperature and humidity-dependent interaction effects on tongue color in diabetic patients: a quantitative analysis and TCM perspective.Frontiers in endocrinology · 2026Article
- Dark red tongue color formation caused by hyperglycemia is attributed to decreased blood flow of tongue tissue partially due to nuclear factor-kappa B pathway activation.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2023Article
- TongueCaps: An Improved Capsule Network Model for Multi-Classification of Tongue Color.Diagnostics (Basel, Switzerland) · 2022Article
- Deep Learning Multi-label Tongue Image Analysis and Its Application in a Population Undergoing Routine Medical Checkup.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- A new method for assessing chronic insomnia: Machine learning-based fusion of TCM observation digital features.Digital healthArticle
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
Abstract
purposeStudies have shown the association between tongue color and diseases. To help clinicians make more objective and accurate decisions quickly, we take unsupervised learning to deal with the basic clustering of tongue color in a 2D way.
methodsA total of 595 typical tongue images were analyzed. The 3D information extracted from the image was transformed into 2D information by principal component analysis (PCA). K-Means was applied for clustering into four diagnostic groups. The results were evaluated by clustering accuracy (CA), Jaccard similarity coefficient (JSC), and adjusted rand index (ARI).
resultsThe new 2D information totally retained 89.63% original information in the L*a*b* color space. And our methods successfully classified tongue images into four clusters and the CA, ARI, and JSC were 89.04%, 0.721, and 0.890, respectively.
conclusionsThe 2D information of tongue color can be used for clustering and to improve the visualization. K-Means combined with PCA could be used for tongue color classification and diagnosis. Methods in the paper might provide reference for the other research based on image diagnosis technology.
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