• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.296-299
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• 2000

본 연구는 컴퓨터 비전 시스템을 위한 라이브러리를 설계 및 구현하고, 이를 적용하여 적정량의 정액 내에 분포되어 있는 정자의 수를 측정하는 불임진단보조용 시스템을 개발하였다. 본 시스템은 육안으로 검사하던 수작업을 자동화하여 의사의 주관적 진단에 신뢰도 , 높은 수치화된 정보를 제공할 수 있다. 또한 범용 주변 장비와 윈도우즈 환경을 사용함으로써 경제성, 확장성, 호환성을 가질 뿐만아니라 윈도우즈 사용자에게 친숙하고 편리한 인터페이스를 제공할 수 있다. 개발된 시스템의 성능을 병원에서 제공된 영상으로 테스트하였다.

• 전기의세계
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• v.64 no.7
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• pp.16-25
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• 2015

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.23 no.10 s.197
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• pp.53-60
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• 2005

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.358-366
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• 2012

Cirrhosis is a consequence of chronic liver disease characterized by replacement of liver tissue by fibrosis, scar tissue and regenerative nodules leading to loss of liver function. Liver Cirrhosis is most commonly caused by alcoholism, hepatitis B and C, and fatty liver disease, but has many other possible causes. Some cases are idiopathic disease from unknown cause. Abdomen of liver Computed tomography(CT) is one of the primary imaging procedures for evaluating liver disease such as liver cirrhosis, Alcoholic liver disease(ALD), cancer, and interval changes because it is economical and easy to use. The purpose of this study is to detect technique for computer-aided diagnosis(CAD) to identify liver cirrhosis in abdomen CT. We experimented on the principal components analysis(PCA) algorithm in the other method and suggested texture information analysis(TIA). Forty clinical cases involving a total of 634 CT sectional images were used in this study. Liver cirrhosis was detected by PCA method(detection rate of 35%), and by TIA methods(detection rate of 100%-AGI, TM, MU, EN). Our present results show that our method can be regarded as a technique for CAD systems to detect liver cirrhosis in CT liver images.

• Journal of the Korean Society of Radiology
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• v.10 no.2
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• pp.81-87
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• 2016

In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some fatty liver patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of fatty liver. As the results of examining over 30 example CT images of fatty liver, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including Average Gray Level, Entropy 96.67%, Skewness 93.33%, and Smoothness while others showed a little low disease recognition rate: 83.33% for Uniformity 86.67% and for Average Contrast 80%. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of fatty liver and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.

• Journal of the Korean Society of Radiology
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• v.10 no.8
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• pp.645-652
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• 2016

In this study, based on the analysis of texture feature values of statistical properties. And we examined the normal and the applicability of the computer-aided diagnosis of cerebral infarction in the brain computed tomography images. The experiment was analyzed to evaluate the ROC curve recognition rate of disease using six parameters representing the feature values of the texture. As a result, it showed average mean 88%, variance 92%, relative smoothness 94%, uniformity of 88%, a high disease recognition rate of entropy 84%. However, it showed a slightly lower disease recognition rate and 58% for skewness. In the analysis using ROC curve, the area under the curve for each parameter indicates 0.886 (p = 0.0001) or more, resulted in a meaningful recognition of the disease. Further, to determine the cut-off values for each parameter are determined to be the prediction of disease through the computer-aided diagnosis.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.23-30
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• 2010

With the advancement of information technology and increasing diversity in medical field, there are ongoing researches on ontology based intelligent medical system in Oriental medicine field. Intelligent diagnostic support system uses ontology to give a structure to complex medical knowledge and personal medical history so that we can make diagnosis more scientific, and provide better medical services. In this paper, we suggest an ontology that structuralize three knowledge types basic medical data, clinical trial data, and personal health information, which can be used as important information for individually tailored diagnosis. Especially in Oriental medicine diagnosis, both patient's symptoms of illness and physical constitution play a great role; it can lead to distinct diagnosis depending on their combination. Thus, it is much needed to have a diagnostic support system that uses personal health history and physical constitution along with basic medical data and clinical trial data in the field. In this paper, we implemented an Oriental medicine diagnostic support system that provides individualized diagnosis service to each patient by building an ontology on Oriental medicine focused on individual physical constitution and disease information.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.362-369
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• 2014

This study aimed to propose an accurate diagnostic method for osteoporosis by realizing a computer-aided diagnosis system with the application of the statistical analysis of texture features using digital images of lateral lumbar spine of patients with osteoporosis and providing reliable supplementary diagnostic information by model experimental research for early diagnosis of diseases. For these purposes, digital images of lateral lumbar spine of normal individuals and patients with osteoporosis were used in the experiments, and the values of statistical texture features on the set ROI were expressed in six parameters. Among the texture feature values of the six parameters of osteoporosis, the highest and lowest recognition rates of 95 and 80% were shown in average gray level and uniformity, respectively. Moreover, all the six parameters showed recognition rates of over 80% for osteoporosis: 82.5% in average contrast, 90% in smoothness, 87.5% in skewness, and 87.5% in entropy. Therefore, if a program developing into a computer-aided diagnosis system for medical images is coded based on the results of this study, it is considered possible to be applied to preliminary diagnostic data for automatic detection of lesions and disease diagnosis using medical images, to provide information for definite diagnosis of diseases, to diagnose by limited device, and to be used to shorten the time to analyze medical images.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.11-18
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• 2014

In this paper, we propose a self-diagnosis system that is based on the ART2 algorithm in order to extract more detailed disease information by fuzzy reasoning method especially when the boundary of perceived symptoms are not clearly classified into disease categories. With that modification from previous version of the self health pre-diagnosis system, the proposed one is verified as more effective by field experts' evaluation as an intelligent assistant tool for public users before they consult with medical experts.

• Journal of the KSME
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• v.25 no.6
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• pp.466-476
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• 1985

이제 기계기술은 전자기술과 더불어 새로운 메카트로닉스(mechatronics)를 구성하여 한 분야로 발전하고 있다. 현재 우리의 천연자원은 빈약하고 고도의 경제성장을 지속적으로 이룩하기 위해, 기계기술분야 중에서도 기술집약적이고 고부가가치를 창출할 수 있는 분야를 개척하므로써, 수 입대체와 수출수요 창출효과를 기대할 수 있다. 메카트로닉스 제품은 산업상 모든 분야에 적 용되나 특히 정보기기의 경우 모든 제품이 이에 해당된다. 여기에는 컴퓨터, 보조기억장치, 터 어미녈, 프린터, 팩시밀리, PPC(Plain Paper Copier), 모뎀(modem), 워드프로세서, 전자식 타자기 등등 여러 제품이 있다. 본 고에서는 지면관계상 이중에서 우리가 중점 개발투자로 역점을 두 고자 하는 컴퓨터 주변기기들의 현황을 진단해 보고 타 분야에 대해서는 다음 기호에 언급하기로 하겠다.