• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.801-804
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• 2013

미각의 종류별 구획에 따른 설진 모델을 제안한다. 시스템의 전체 구성은 혀 영상획득, 혀 영역 검출, 혀 영역 분할, 분할 영역의 색상분포 검출, 이상 유무 판별로 구성된다. 혀의 DB는 정상 및 비정상 혀로 분류되었으며 실제 한방병원에 내원하는 환자들의 혀 사진으로 구축하였다. 혀 영역으로부터 짠맛, 신맛, 단맛, 쓴맛의 네 가지 영역으로 나누어 분할하고, HSI 컬러모델을 이용하여 색상분석을 시행하였다. 이때, 주변 조도의 영향을 최소화하기 위하여 I(Intensity)값을 제외한 H(Hue)와 S(Saturation) 성분의 히스토그램을 이용하여 색상을 분석하였다. 제안하는 색상분석 진단모델과 한의학 전문의의 진단 결과를 비교하여 미각별 영역의 이상 유무를 판단하였다. 제안하는 설진 알고리즘으로 판단한 결과 87.5%가 전문의의 분류의 결과 일치함을 확인하였다.

• 한국한의학연구원논문집
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• 제13권2호통권20호
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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.

• 대한한의진단학회지
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• 제17권2호
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• pp.77-89
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• 2013

Objectives Tongue diagnosis is an important diagnostic method in traditional Eastern medicine, and it has a high potential to be used in the future healthcare because of easy, quick, and non-contact measuring features. Recently, research and development efforts on computerized tongue diagnosis systems (CTDS) have been active that led to the technical advancements in the field of photographing techniques, image extraction and classification algorithms. In this study, we analyzed the trends in the CTDS patents. Using the WIPS search engine (www.wipsglobal.com), quantitative and qualitative patent analyses were performed through Korea, China, Japan, U.S.A and Europe. Methods For a systematic search and data analysis, we defined patent categories based on the application area and technical details. By applying thus-obtained categorical key words, we obtained 360 relevant patents on photographing techniques, image extraction and classification algorithms for the purpose of diagnosis or security. Results As a result, companies related to image acquisition, medical imaging and mobile devices and research groups of universities in East Asia were major patent applicants. In all the five countries, the number of patents have been increasing since 1980. In particular, technology related to color correction and image segmentation were most actively patented categories, and expected to continue a high application rate.

• 산업경영시스템학회지
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• 제46권3호
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• pp.1-6
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• 2023

In the realm of dental prosthesis fabrication, obtaining accurate impressions has historically been a challenging and inefficient process, often hindered by hygiene concerns and patient discomfort. Addressing these limitations, Company D recently introduced a cutting-edge solution by harnessing the potential of intraoral scan images to create 3D dental models. However, the complexity of these scan images, encompassing not only teeth and gums but also the palate, tongue, and other structures, posed a new set of challenges. In response, we propose a sophisticated real-time image segmentation algorithm that selectively extracts pertinent data, specifically focusing on teeth and gums, from oral scan images obtained through Company D's oral scanner for 3D model generation. A key challenge we tackled was the detection of the intricate molar regions, common in dental imaging, which we effectively addressed through intelligent data augmentation for enhanced training. By placing significant emphasis on both accuracy and speed, critical factors for real-time intraoral scanning, our proposed algorithm demonstrated exceptional performance, boasting an impressive accuracy rate of 0.91 and an unrivaled FPS of 92.4. Compared to existing algorithms, our solution exhibited superior outcomes when integrated into Company D's oral scanner. This algorithm is scheduled for deployment and commercialization within Company D's intraoral scanner.