• The Journal of the Society of Korean Medicine Diagnostics
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• v.14 no.2
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• pp.67-74
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• 2010

Objectives: Tongue moisture is one of major features in tongue diagnosis of Oriental Medicine. But with regard to the methods to qualify the tongue moisture level, there have been no adequate modalities to satisfy clinicians' needs. So we developed an novel device and method to quantify the tongue moisture level without contact. Methods and Materials: Ratio of saturated area to total tongue area in the image captured with a spot light at various angles was calculated. We regarded that ratio represented the moisture of tongue surface. To evaluate the performance of suggested method, we observed the correlation between conventional contact method and our method with 19 healthy subjects. Results: With comparison to conventional contact method (Schirmer test), the suggested method showed good correlation (R = 0.8602, R2 = 0.7399). Conclusion: This Method could be a convenient and robust method to evaluate tongue moisture.

• Korean Journal of Oriental Medicine
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• v.14 no.3
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• pp.97-102
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• 2008

The tongue diagnosis is a diagnostic method in the oriental medicine that uses shape, substance, coating, and movement of the tongue to determine the condition of health and disease characteristics in human. Since this information, however, could be affected by subjective sense and visual information, it is difficult to obtain the objective and reproducible results. This research aims at building a reproducible tongue diagnosis system using color chart that is attached close to the face contact region. The picture of color chart is taken simultaneously with a tongue and applied to color revision. The system, in addition, is focused on providing a clear tongue image through securing a sufficient photographing distance with a surface coating mirror. The lightning part which can suppress the reflection by sputum in maximum is implemented for the objectification and quantification of the tongue diagnosis system. The face contact region is designed for consideration of a testee's convenience. To evaluate the reproducibility of the system, the CVs (coefficient of variance, %) of $L{\ast}$, $a{\ast}$ and $b{\ast}$ of red, green and blue regions in color chart are calculated, respectively. The results of all CVs shows that the tongue diagnosis system is re liable and those consequences contribute to the objectification and quantification of the tongue diagnosis system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2051-2057
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• 2007

In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.221-228
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• 2014

The color and shape of the tongue reflect the physiological and clinico-pathological condition of the body. Recently, various tongue image acquisition devices have been developed for accurate diagnosis based on quantitative and objective tongue features. Since a color information is essential for tongue diagnosis, the performance of an illuminator is very important for the tongue image acquisition device. In this study, we developed an indirect illumination, which is possible to improve a homogeneity of light intensities on the tongue surface, and evaluated its performances. In order to realize the indirect illumination (II), a semi-ellipsoidal solid structure (SESS) for the light reflex was located in the system, and two high-brightness white LEDs were placed for illuminating the areas under frontal camera in the SESS. The tongue surface was illuminated by reflected light from the SESS. The light homogeneity induced by three different illuminations including the II was evaluated by calculating coefficient of variation (CV) of illuminance of five regions. The II showed less than 0.01 of CV and the direct illumination (DI) and the direct illumination with a light diffusion plate (DILDP) showed 0.16 and 0.13, respectively. The reflexed pixel ratios of tongue phantom images show 5.76%, 4.22%, 1.79% for the DI, the DILDP and the II, respectively. The homogeneity of a tongue phantom was evaluated by calculating CV of mean pixel values of six different tongue regions, and showed less than 0.06 in the II. If the II technique apply to tongue diagnosis system, it is expected to improve diagnostic accuracy in clinic.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.123-131
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• 2008

In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of one's health like the physiological and the clinicopathological changes of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition a lot. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue region from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmenting, detecting the edge with a local minimum over a shading area from the structure of a tongue, correcting local minima or detecting the edge with the greatest color difference, selecting one edge to correspond to a tongue shape, and smoothing edges, where preprocessing consists of down-sampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue. Finally, the systematic procedure separated only a tongue region from a face image with a tongue, which was obtained from a digital tongue diagnosis system. Oriental medical doctors' evaluation for the results illustrated that the segmented region excluding a non-tongue region provides important information for the accurate diagnosis. The proposed method can be used for an objective and standardized diagnosis and for an u-Healthcare system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.313-322
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• 2020

A large volume of data will improve the robustness of deep learning models and avoid overfitting problems. In automatic tongue segmentation, the availability of annotated tongue images is often limited because of the difficulty of collecting and labeling the tongue image datasets in reality. Data augmentation can expand the training dataset and increase the diversity of training data by using label-preserving transformations without collecting new data. In this paper, augmented tongue image datasets were developed using seven augmentation techniques such as image cropping, rotation, flipping, color transformations. Performance of the data augmentation techniques were studied using state-of-the-art transfer learning models, for instance, InceptionV3, EfficientNet, ResNet, DenseNet and etc. Our results show that geometric transformations can lead to more performance gains than color transformations and the segmentation accuracy can be increased by 5% to 20% compared with no augmentation. Furthermore, a random linear combination of geometric and color transformations augmentation dataset gives the superior segmentation performance than all other datasets and results in a better accuracy of 94.98% with InceptionV3 models.

• The Journal of Korean Medicine
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• v.27 no.2 s.66
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• pp.134-144
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• 2006

Tongue diagnosis is an important diagnostic method in traditional Oriental medicine. It has been especially accepted that quantitative analysis of tongue images allows the accurate diagnosis of the exterior-interior and cold-heat patterns of a patient. However, to ensure stable and reliable results, the color reproduction of such images must first be error-tree. Moreover, tongue diagnosis is much influenced by the surrounding illumination and subjective color recognition, so it has to be performed objectively and quantitatively using a digital diagnostic machine. In this study, 457 tongue images of outpatients were collected using the Digital Tongue Inspection System. Through statistical analysis, the result shows that the heat and cold patterns can be distinguished clearly based on the hue value of the tongue images. The average hue value (1.00) of the tongue's image in the cold pattern is higher than that in the heat pattern (0.99).

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.37-47
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• 2021

In this paper, we propose a new deep learning model for tongue segmentation with improved accuracy compared to the existing model by diversifying the receptive field in the U-net. Methods such as parallel convolution, dilated convolution, and constant channel increase were used to diversify the receptive field. For the proposed deep learning model, a tongue region segmentation experiment was performed on two test datasets. The training image and the test image are similar in TestSet1 and they are not in TestSet2. Experimental results show that segmentation performance improved as the receptive field was diversified. The mIoU value of the proposed method was 98.14% for TestSet1 and 91.90% for TestSet2 which was higher than the result of existing models such as U-net, DeepTongue, and TongueNet.

• Korean Journal of Oriental Medicine
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• v.14 no.3
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• pp.89-95
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• 2008

A tongue shows physiological and clinicopathological changes of inner organs. Visual inspection of a tongue is not only convenient but also non-invasive. To develop an automat ic tongue diagnosis system for an objective and standardized diagnosis, the separation of the tongue are a from a facial image and the detection of coatings, spots and cracks are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth as well as those of tongue furs and body are similar. The propose d method includes preprocessing with down-sampling and edge enhancement, over-segmentation, detecting positions with a local minimum over shading from the structure of a tongue, and correcting local minima or detecting edge with color difference. The proposed method produces the region of a segmented tongue, and then decomposes the color components of the region into hue, saturation and brightness, resulting in classifying the regions of tongue furs(coatings) into kinds of coatings and substance and segmenting them. Spots are detected by using local maxima and the variation of saturation, and cracks are searched by using local minima and the directivity of dark areas in brightness. The results illustrate the segmented region with effective information, excluding a non-tongue region and also give us accurate discrimination of coatings and the precise detection of spots and cracks. It can be used to make an objective and standardized diagnosis for an u-Healthcare system as well as a home care system.