• 동의생리병리학회지
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• 제19권5호
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• pp.1437-1442
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• 2005

Tongue Diagnosis is the important traditional oriental medical diagnosis method that observes not only the general physiological state but also some kinds of disease. However, manual tongue diagnosis is much influenced by surrounding illumination. Therefore, Digital Tongue Inspection System(DigiTis) is needed for the quantification of objective tongue information, In this research, Tongue images of 98 malignant Neoplasm patients and 34 normal persons were collected by Digital Tongue Inspection System. Statistical analysis of tongue images and patient data indicates that cancer group has more blue-purple components in tongue body(舌質) and yellow components in tongue coating than normal group. Also, there are a lot of rose-pink components in the cancer group of second stage and blue-purple components in the cancer group of third or fourth stage. Our study shows that tongue image is a useful index for distinction between disease and health. Furthermore we need more extended research through the additional sampling and various disease.

• 대한기관식도과학회지
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• 제17권1호
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• pp.14-18
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• 2011

The diagnosis and treatment of early gastrointestinal cancers is the gastroenterologists' mission because of national cancer screening program in South Korea. The detection of early cancers is emphasized, because these were previously treated with surgical treatment can be currently cured with endoscopic treatment. Gastroenterologists who achieved at least on some level can make an exact diagnosis regardless of what type of endoscopy, but generally, there are some required conditions for an optimal diagnosis. First, clinically important lesions have to be detected easily. Second, the border and morphology of lesions have to be characterized easily. Third, lesions have to be diagnosed exactly. Precancers and early cancers are often subtle and can pose a challenge to gastroenterologists to visualize using standard white light endoscopy. The use of dye solutions aids the diagnosis of early gastrointestinal cancers, however, it is a quite cumbersome to use dye solutions all the time and the solution often bothers the exact observation by pooling into the depression or ulceration of the lesion. To overcome this weakness, newer endoscopes are now developed so called "image enhanced endoscopy" using optical and/or electronic methods such as narrow band imaging (NBI), autofluorescence imaging (AFI), i-scan, flexible spectral imaging color enhancement (FICE) and confocal endomicroscopy (CLE).

• 한국실내디자인학회논문집
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• 제18호
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• pp.74-80
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• 1999

Chinese medicine hospital enables the users to expect more efficient cure result in the psychological stability and the comfortable indoor environment by supplying the functional and aesthetic cure space with the medical action of good quality Medical activity is to treat the human life. Thus, hospital must be more human-centered-place than other space. Thus study is establishment of space to be able to lead more rational and active participation than the conservative and passive image of the department of diagnosis and treatment for outpatients is desirable. This study is the indoor schedule to suggest the direction about the department of diagnosis and treatment for outpatients of Chinese medicine hospital of native image with more comfortable and positive approach on the basis of above points at issues as the schedule to fulfill the performance of medical function and the emotional and psychological satisfaction of users as the human being-centered-medical institution on the subject of the department of diagnosis and treatment for outpatients in Chinese medicine hospital. And, this researcher progressed as follows by being premised on this 1. Description of Goai, Range and Method of Study and Suggestion of Study Direction 2. Concept introduction as the Basic Approach of Theory which is necessary for Study 3. The Problems were recognized by grasping the present condition in Korea through the questionaines 4. establishment of Concept and direction which are necessary for planning the indoor of the department of Diagnosis and Treatment for Chinese Medicine Hospital 5. Progression of Design Plan attendant upon Concept 6. Analysis of the Conents attendant upon this, and Conclusiov.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.69-77
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• 2018

The malignant melanoma accounts for about 1 to 3% of the total malignant tumor in the West, especially in the US, it is a disease that causes more than 9,000 deaths each year. Generally, skin lesions are difficult to detect the features through photography. In this paper, we propose a computer-aided diagnosis algorithm based on deep learning for classification of malignant melanoma and benign skin tumor in RGB channel skin images. The proposed deep learning model configures the tumor lesion segmentation model and a classification model of malignant melanoma. First, U-Net was used to segment a skin lesion area in the dermoscopic image. We could implement algorithms to classify malignant melanoma and benign tumor using skin lesion image and results of expert's labeling in ResNet. The U-Net model obtained a dice similarity coefficient of 83.45% compared with results of expert's labeling. The classification accuracy of malignant melanoma obtained the 83.06%. As the result, it is expected that the proposed artificial intelligence algorithm will utilize as a computer-aided diagnosis algorithm and help to detect malignant melanoma at an early stage.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• Tuberculosis and Respiratory Diseases
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• 제57권6호
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• pp.515-521
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• 2004

With the increasing resolution of modern CT scanners, analysis of the larger numbers of images acquired in a lung screening exam or diagnostic study is necessary, which also needs high accuracy and reproducibility. Recent developments in the computerized analysis of medical images are expected to aid radiologists and other healthcare professional in various diagnostic tasks of medical image interpretation. This article is to provide a brief overview of some of computer-aided diagnosis schemes in chest CT.

• 대한영상의학회지
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• 제84권1호
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• pp.150-169
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• 2023

다발성 골수종은 골수에서 클론 형질 세포의 증식으로 인한 악성 혈액 질환으로 최근 우리나라에서도 발병률이 증가하고 있다. 다발성 골수종의 치료법이 발전하면서 질환의 조기 진단과 조기 치료의 필요성이 대두되었고 International Myeloma Working Group (이하 IMWG) 중심으로 질병의 진단의학적, 영상의학적 진단 기준이 여러 차례 개정되고 있다. 또한 다발성 골수종 환자의 진단과 치료 반응 평가에 전신 자기공명영상(whole body MR; 이하 WBMR)의 사용량이 증가하면서 WBMR의 영상 획득 기법이나 영상 결과 해석, 반응평가법을 표준화하기 위해 Myeloma Response Assessment and Diagnosis System (이하 MYRADS)가 만들어졌다. 이 종설에서는 다발성 골수종의 정확한 진단을 위해 영상의학과 의사로서 알아야 할 최신 지견으로 IMWG의 최신 가이드라인에 따른 다발성 골수종의 영상검사법 및 MY-RADS에 따른 WBMR에서의 영상 획득 기법 및 반응 평가 기법에 대해 설명하였다.

• 대한임베디드공학회논문지
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• 제18권6호
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• pp.285-292
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• 2023

With the wide spread of smart farms and the advancements in IoT technology, it is easy to obtain additional data in addition to crop images. Consequently, deep learning-based crop disease diagnosis research utilizing multimodal data has become important. This study proposes a crop disease diagnosis method using multimodal supervised contrastive learning by expanding upon the multimodal self-supervised learning. RandAugment method was used to augment crop image and time series of environment data. These augmented data passed through encoder and projection head for each modality, yielding low-dimensional features. Subsequently, the proposed multimodal supervised contrastive loss helped features from the same class get closer while pushing apart those from different classes. Following this, the pretrained model was fine-tuned for crop disease diagnosis. The visualization of t-SNE result and comparative assessments of crop disease diagnosis performance substantiate that the proposed method has superior performance than multimodal self-supervised learning.

• 재활간호학회지
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• 제7권2호
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• pp.127-139
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• 2004

Purpose: This study was to investigate the degree of body image, self esteem and quality of life, to identify general and disease of characteristics on influencing this factors with the intention of providing basal data for developing nursing intervention to promote body image, self esteem and quality of life. Method: Subjects of this study were 91 grown-up congenital heart patients over 18 years in 2 tertiary hospitals. The data on body image, self esteem and quality of life were collected through questionnaire from March to April 2004. The data were analyzed by descriptive statistics, t-test, Pearson's correlation, ANOVA and tukey test using SAS for Windows 8.1 program. Result: 1) The mean scores of body image, self esteem and quality of life were 63.01, 25.29 and 496.79. 2) Body image was correlated with age(p=.0239), educational level(p=.0182), diagnosis(p=.0066), number of operation(p=.0148), cyanosis(p<.0001), complication(p=.0096) and NYHA level(p=.0378). 3) Self esteem was correlated with education level(p=.0026), economic level(p=.0240), number of operation(p=.0113) and cyanosis (p=.0006). 4) Quality of life was correlated with age(p=.0432) and diagnosis(p=.0020), number of operation (p=.0063), duration of last operation(p=.0225), cyanosis(p<.0001), complication(p=.0090) and NYHA level(p<.0001). 5) There was significantly positive relationship between body image, self esteem and quality of life. Subjects with more positive body image had higher self esteem(r=.7897, p<.05) and subjects with higher self esteem had higher quality of life(r=.6091, p<.05).

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.1411-1412
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• 2013