Abstract

Tongue diagnosis is a distinctive diagnostic technique for traditional Chinese medicine (TCM). It plays an important role as a fundamental basis for diagnosing diseases and syndromes in TCM, focusing on tongue texture and tongue fur. Tongue fur mainly includes tongue fur texture and tongue fur color. Especially latter is an important indicator to identify the nature of the disease. In clinical practice, tongue fur can easily be influenced by medications and dietary intake, resulting in color illusion and misdiagnosis. This dataset records two types of tongue images of TCM, namely stained tongue fur and non-stained tongue fur, with an average of about 1,000 tongue images for each type. The stained tongue fur data include the color change images of the tongue fur captured at intervals of 5 minutes, 10 minutes, and 30 minutes after consuming food that causes staining in health conditions of different populations. The colors are can be primarily categorized into three categories: white, yellow, and gray/black, with yellow being the most prevalent. Non-stained tongue fur data include pathological tongue fur images of different populations, falling into white, yellow, and gray/black. This dataset can serve as a reliable classification basis for the research in the field of tongue diagnosis and effectively solve the problem of tongue fur artifacts. Moreover, it can provide valuable data to support the advancement of more intelligent tongue diagnosis instruments.

Full Text
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