Tongue image segmentation via thresholding and clustering

Li, Zuoyong; Zhao, Yu; Liu, Weixia; Hu, Jinmei; Lin, Yaming; Zhang, Zuchang

doi:10.1109/cisp-bmei.2017.8302207

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…The tongue segmentation technique of the color model conversion method has gradually matured. [11] proposed to first find an initial object region, by transforming and thresholding the morphological components of the image in the HSI color space and morphological operations, and then image clustering the RGB components of the initial object region to find the root of the tongue. The gap region between the upper lip and the upper lip is finally removed by means of the gap region to remove the false tongue region such as the upper lip, and the tongue is extracted from the initial target region.…”

Section: Tongue Segmentation Algorithmmentioning

confidence: 99%

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

Zhou¹,

Peng²,

Gao³

et al. 2019

J Multimed Inf Syst

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In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

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Section: Tongue Segmentation Algorithmmentioning

confidence: 99%

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

Zhou¹,

Peng²,

Gao³

et al. 2019

J Multimed Inf Syst

View full text Add to dashboard Cite

show abstract

“…The first type is based on the classical mathematical model, such as threshold method [ 5 ], since the color of the tongue is usually red. For instance, Gu et al [ 6 ] utilized an automatic tongue segmentation algorithm based on the threshold, whose experiment results show that the segmented area is complete and close to the actual target.…”

Section: Introductionmentioning

confidence: 99%

Intelligent quality control of traditional chinese medical tongue diagnosis images based on deep learning

Zhou,

Li,

et al. 2024

THC

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BACKGROUND: Computer-aided tongue and face diagnosis technology can make Traditional Chinese Medicine (TCM) more standardized, objective and quantified. However, many tongue images collected by the instrument may not meet the standard in clinical applications, which affects the subsequent quantitative analysis. The common tongue diagnosis instrument cannot determine whether the patient has fully extended the tongue or collected the face. OBJECTIVE: This paper proposes an image quality control algorithm based on deep learning to verify the eligibility of TCM tongue diagnosis images. METHODS: We firstly gathered enough images and categorized them into five states. Secondly, we preprocessed the training images. Thirdly, we built a ResNet34 model and trained it by the transfer learning method. Finally, we input the test images into the trained model and automatically filter out unqualified images and point out the reasons. RESULTS: Experimental results show that the model’s quality control accuracy rate of the test dataset is as high as 97.06%. Our methods have the strong discriminative power of the learned representation. Compared with previous studies, it can guarantee subsequent tongue image processing. CONCLUSIONS: Our methods can guarantee the subsequent quantitative analysis of tongue shape, tongue state, tongue spirit, and facial complexion.

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Tongue image segmentation via thresholding and clustering

Cited by 2 publications

References 12 publications

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

Intelligent quality control of traditional chinese medical tongue diagnosis images based on deep learning

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