• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.226-231
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• 2019

A WTCI is an important criteria for evaluating an mount of patient's tongue coating in tongue diagnosis. However, Previous WTCI tongue coating evaluation methods is a most of quantitatively measuring ration of the extracted tongue coating region and tongue body region, which has a non-objective measurement problem occurring by exposure conditions of tongue image or the recognition performance of tongue coating. Therefore, a WTCI based on deep learning is proposed for classifying an amount of tonger coating in this paper. This is applying the AI deep learning method using big data. to WTCI for evaluating an amount of tonger coating. In order to verify the effectiveness performance of the deep learning in tongue coating evaluating method, we classify the 3 types class(no coating, some coating, intense coating) of an amount of tongue coating by using CNN model. As a results by testing a building the tongue coating sample images for learning and verification of CNN model, proposed method is showed 96.7% with respect to the accuracy of classifying an amount of tongue coating.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.96-101
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• 2015

A tongue coating evaluation method for WTCI(Winkel Tongue Coating Index) is proposed in this paper, which is used as the diagnostic criteria in the tongue diagnosis. This method uses the color channel analysis and tongue coating extraction from the ultraviolet tongue image. Proposed method analyzes the histogram distribution of the respective color channel for extracting a tongue coating, and performs the verification test from the selected color channel in the tongue coating extraction. Also, Objectivity of the tongue diagnostic criteria is verified by the artificial sample and real-tongue image experiments. In order to evaluate the performance of the proposed Computerized Assistant WTCI Evaluation method, after verifying a measurement accuracy by using the artificial sample images, and applying to the various real-tongue image of subjects. As a result, the proposed WTCI method is very successful.

• The Journal of Internal Korean Medicine
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• v.35 no.2
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• pp.157-174
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• 2014

Objectives : The aims of this study were to evaluate the diagnostic values of tongue coating thickness and sterno-costal angle as the quantitative diagnostic indicators in functional dyspepsia. Methods : We surveyed 60 functional dyspepsia patients recruited by the clinical trial, 'Clinical Trial for Evaluation on Availability of tongue diagnosis system (CTS-1000) : a Pilot study'. The patients were classified into three groups according to Rome III criteria for functional dyspepsia, and categorized into five groups according to Instrument of pattern identification for functional dyspepsia. Nepean dyspepsia index-Korean version (NDI-K) score, tongue coating thickness (percentage of tongue coating by tongue diagnosis system (CTS-1000), and weight of tongue coating by microbalance), sterno-costal angle, duration of illness and body mass index (BMI) were investigated. Results : Among the 5 types by instrument of pattern identification for functional dyspepsia, a significant difference of percentage of tongue coating was found. Percentage of tongue coating and weight of tongue coating showed significant correlation with total NDI-K score. Sterno-costal angle showed strong positive correlation with BMI and also showed significant difference between the non-overweight (BMI<23, n=32) and overweight ($BMI{\geq}23$, n=28) groups. Conclusions : Tongue coating thickness showed its potential as a new quantitative diagnostic indicator of functional dyspepsia. Further studies on the sterno-costal angle are anticipated to evaluate its potential as a new quantitative diagnostic indicator.

• Korean Journal of Oriental Medicine
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• v.13 no.3
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• pp.119-124
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• 2007

Introduction: In Oriental medicine, the status of tongue is the important indicator to diagnose one's health, because it represents physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive, so tongue diagnosis is most widely used in Oriental medicine. By the way, since tongue diagnosis is affected by examination circumstances a lot, its performance depends on a light source, degrees of an angle, a medical doctor's condition etc. Therefore, it is not easy to make an objective and standardized tongue diagnosis. In order to solve this problem, in this study, we tried to design a discriminant function for thick and thin coating with color vectors of preprocessed image. Method: 52 subjects, who were diagnosed as white-coated tongue, were involved. Among them, 45 subjects diagnosed as thin coating and 7 subjects diagnosed as thick coating by oriental medical doctors, and then their tongue images were obtained from a digital tongue diagnosis system. Using those acquired tongue images, we implemented two steps: Preprocessing and image analyzing. The preprocessing part of this method includes histogram equalization and histogram stretching at each color component, especially, intensity and saturation. It makes the difference between tongue substance and tongue coating was more visible, so that we can separate tongue coating easily. Next part, we analyzed the characteristic of color values and found the threshold to divide tongue area into coating area. Then, from tongue coating image, it is possible to extract the variables that were important to classify thick and thin coating. Result : By statistical analysis, two significant vectors, associated with G, were found, which were able to describe the difference between thick and thin coating very well. Using these two variables, we designed the discriminant function for coating classification and examined its performance. As a result, the overall accuracy of thick and thin coating classification was 92.3%. Discussion : From the result, we can expect that the discriminant function is applicable to other coatings in a similar way. Also, it can be used to make an objective and standardized diagnosis.

• Journal of Biomedical Engineering Research
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• v.44 no.4
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• pp.242-254
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• 2023

Although upper respiratory tract infections (URTIs) are common diseases, there have been no studies of their relationship with the indices obtained from tongue image analyses. The purpose of this study was to identify a tongue index through an analysis of tongue images (TIs) showing significant changes before and after treatment in patients with URTIs. A computerized tongue image acquisition system was developed to acquire TIs from subjects in the same environment. An image was taken from each of 39 URTI patients and 39 healthy controls. For the patients, images were acquired before and after treatment to identify changes. The tongue area was classified into a tongue body and a tongue coating, and the coating ratio between the two areas, the average value of the colour of each area, and teeth marks were calculated. No significant difference was observed in age or sex between the URTI patients and control participants. Heart rates were slightly different. The analysis of TIs showed that the luminance of the tongue coating and the coating area ratio were decreased, while the reddish value of the tongue body at the centre area increased as the treatment progressed. Tongue coating and body in URTIs had different colour and shape from those in the normal. It is expected that this result will contribute not only to the objectification of traditional Chinese medicine but also to diagnostic methods that do not involve face-to-face physician visit during the pandemic.

• The Journal of Internal Korean Medicine
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• v.29 no.1
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• pp.258-264
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• 2008

Objectives : The aim of this study was to confirm the characteristics of oral malodor patients by evaluating the differences of salivary flow rate, secretory immunoglobulin A (sIgA) level in saliva between the patient and control groups, and the correlation with the tongue coating, volatile sulfur compound (VSC), salivary flow rate and sIgA level in saliva in the patients group. Methods : Forty-seven patients with oral malodor and twenty healthy volunteers were included in this study. Their tongue coating was assessed with the Winkel tongue coating index, and salivary flow rate, sIgA concentrations in saliva and the level of VSC in oral cavity were measured. Results : There were no significant differences of the salivary flow rate and the sIgA level in saliva between the patient and control groups, but there was a significant relationship between the accumulation of tongue coating and the level of VSC in oral cavity. Conclusions : Our results suggest that tongue coating is closely related to oral malodor, but further studies are needed to confirm the relationship between tongue coating and sIgA level in saliva.

• The Journal of Internal Korean Medicine
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• v.39 no.4
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• pp.637-644
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• 2018

Objectives: In this study, the tongue features of patients with functional dyspepsia (FD) were compared with those of healthy controls. Methods: This prospective, case-control study was conducted on patients with FD and controls recruited at a single center. After screening, the subjects were allocated to the patient or control groups (patients=42, controls=40). Tongue images were acquired using a computerized tongue image acquisition system (CTIS). An independent t-test was conducted to compare the measurements from patients and controls. Binary logistic regression was performed to determine significant differences between the two groups after adjusting for age and sex. Results: The CIE $a^*$ color value in the tongue coating area was significantly lower in the patients with FD than in the controls (p=0.001). The tongue coating ratios were also significantly higher in the FD group than in the control group (p=0.003). We found that the CIE $a^*$ color value in the tongue coating area and the tongue coating ratios were significant predictive factors in both groups, based on binary regression analysis (p=0.016, 0.044, respectively). Conclusions: This study found that FD was significantly associated with CIE $a^*$ color value in the tongue coating area and tongue coating ratios. We suggest that these factors could be used as objective indicators of FD.

• Korean Journal of Oriental Medicine
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• v.13 no.2 s.20
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• pp.47-52
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• 2007

In Oriental medicine, the status of tongue is the important indicator to diagnose one's health, because it represents physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive, therefore, tongue diagnosis is one of the most widely used in Oriental medicine. But tongue diagnosis is affected by examination circumstances a lot. It depends on a light source, degrees of an angle, doctor's condition and so on. So it is not easy to make an objective and standardized tongue diagnosis. As part of way to solve this problem, in this study, we tried to design a discriminant function for white and yellow coating with multi-dimensional color vectors. There were 62 subjects involved in this study, among them 48 subjects diagnosed as white-coated tongue and 14 subjects diagnosed as yellow-coated tongue by oriental doctors. And their tongue images were acquired by a well-made Digital Tongue Diagnosis System. From those acquired tongue images, each coating section were extracted by oriental doctors, and then mean values of multi -dimensional color vectors in each coating section were calculated. By statistical analysis, two significant vectors, R in RGB space and H in HSV space, were found that they were able to describe the difference between white coating section and yellow coating section very well. Using these two values, we designed the discriminant function for coating classification and examined how good it works. As a result, the overall accuracy of coating classification was 98.4%. We can expect that the discriminant function for other coatings can be obtained in a similar way. Furthermore, if an automated segmentation algorithm of tongue coating is combined with these discriminant functions, an automated tongue coating diagnosis can be accomplished.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.1
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• pp.97-103
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• 2009

The status and the property of a tongue are the important indicators to diagnose one's health like physiological and clinicopathological changes of inner organs. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, classifying tongue coating is inevitable but difficult since the features like color and texture of the tongue coatings and substance have little difference, especially in the neighborhood on the tongue surface. The proposed method has two procedures; the first is to acquire the color table to classify tongue coatings and substance by automatically separating coating regions marked by oriental medical doctors, decomposing the color components of the region into hue, saturation and brightness and obtaining the 2nd order discriminant with statistical data of hue and saturation corresponding to each kind of tongue coatings, and the other is to apply the tongue region in an input image to the color table, resulting in separating the regions of tongue coatings and classifying them automatically. As a result, kinds of tongue coatings and substance were segmented from a face image corresponding to regions marked by oriental medical doctors and the color table for classification took hue and saturation values as inputs and produced the classification of the values into white coating, yellow coating and substance in a digital tongue diagnosis system. The coating regions classified by the proposed method were almost the same to the marked regions. The exactness of classification was 83%, which is the degree of correspondence between what Oriental medical doctors diagnosed and what the proposed method classified. Since the classified regions provide effective information, the proposed method can be used to make an objective and standardized diagnosis and applied to an ubiquitous healthcare system. Therefore, the method will be able to be widely used in Oriental medicine.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.175-182
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• 2014

Development of an objective diagnosis index for diagnosing a the beginning nature of a disease is the most one of tongue diagnosis in the oriental medicine. However, previous systems have a difficult problem in the creation of objective diagnosis index, and focused on the expert system that can diagnose automatically without an oriental doctor behavior. Therefore, computerized assistant diagnosis software for calculating an optimized diagnosis index is proposed in this paper. This software is operated by the diagnosing behavior of oriental doctor. As developed software is a semi-automatic system, manual method is used to segment a tongue body. Futhermore, numerical diagnosis indices including the color information of non-tongue coating and tongue coating, WTCI are provided to oriental doctor automatically and real-timely. Also, probability estimation value for classifying no coating, thin coating, and thick coating is presented by using the tongue coating area ratio, and EMR chart can use for convenience of diagnosis. In order to evaluate the effectiveness of the our developed software, after building a various tongue image from 60 subjects, we experimented on diagnosis image with our software. As a result, the developed software showed the 95% use-effectiveness of subjects.