• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.599-602
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• 2004

최근 국내 여성의 유방암 발생율은 1위를 차지하며 그 비율 또한 나날이 늘어가고 있는 추세이다. 하지만 유방암은 다른 암에 비해 5년간 관찰 생존율이 약 76%로 갑상선에 이어 두 번째의 생존율을 보이며, 이는 조기발견의 중요성을 다시 한번 상기시키게 한다. 하지만 국내에서 사용되는 유방암 조기검진 방법에는 Mammography(유방촬영술)와 초음파 진단 두 가지가 주를 이루고 있으나 촬영과정 및 장비에 따른 오차로 인한 객관화된 정보생성 부족 및 전달의 부족으로 문제점이 대두되고 있다. 본 연구에서는 Mamography 및 초음파 유방 진단술을 이용하여 전문의의 의사결정에 도움을 줄 수 있는 CAD(Computer Aided Diagnosis) 시스템의 유방암 진단의 특징을 이용, 전문의 관점의 모델링을 기술해보고자 한다.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.79-84
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• 2016

A novel diagnosis scheme PCADP(personalized computer aided diagnosis probability) is proposed to overcome the problems mentioned above. PCADP scheme is a personalized diagnosis method based on ontology and it makes the bio-data analysis just a 'process' in the Smart healthcare service system. In addition, we offer a semantics modeling of the smart healthcare ontology framework in order to describe smart healthcare data and service specifications as meaningful representations based on this PCADP. The PCADP scheme is a kind of statistical diagnosis method which has real-time processing, characteristics of flexible structure, easy monitoring of decision process, and continuous improvement.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.13-18
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• 2004

최근 몇 년간 방사선 의학진단과 관련된 연구가 한층 높아진 가운데 유방암은 여성의 암 중에서 1위를 차지하고 조기에 진단하고 치료하기 위한 국가적인 노력이 필요한 시점이다. 이렇듯 여성들의 유방암 발생빈도수가 급증하면서 대두 되고 있는 것이 조기 진단방법인 Mammography와 초음파 진단이며 그로인하여 발생하는 오진률 역시 많은 연구가 진행 되고 있다. 먼저 Mammography 및 초음파 진단의 문제점 보면 첫째 촬영과정에서의 오차, 둘째 영상의 선명도 ,셋째 전문의의 판독에 대한오차, 넷째 의사의 경험으로 진단함으로 표준화가 존재하지 않는다는 공통적인 문제점을 가지고 있다. 본 연구에서는 CAD 시스템의 프레임웍 및 요소 기술을 제시하여 의사의 진단을 보조적 수행이 보다 수월하도록 하고자 한다. 본 연구에서는 CAD시스템의 기능은 Detection기능(Image enhancement, Morphology, segment detection)과 Diagnosis기능( Neural Natwork등을 이용하여 증상을 판단)이다. 또한 과거 자료를 이용한 변이 및 변화를 예측함으로써 향후 있을 위험요소에 대비가 가능한 모듈과 전문의사가 대화형으로 빠르게 진단지식을 구축할 수 있는 지능형, 대화형 온라인 진단기능을 추가함으로써 외국의 CAD시스템과는 많은 차이가 있다고 볼 수 있다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.928-933
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• 2018

Nowadays, gastropathy is a common disease. As endoscopic equipment are developed and used widely, it is possible to provide a large number of endoscopy images. Computer-aided Diagnosis (CADx) systems aim at helping physicians to identify possibly malignant abnormalities more accurately. In this paper, we present a CADx system to detect and classify the abnormalities of gastric lesions which include bleeding, ulcer, neuroendocrine tumor and cancer. We used an Inception module based deep learning model. And we used data augmentation for learning. Our preliminary results demonstrated promising potential for automatically labeled region of interest for endoscopy doctors to focus on abnormal lesions for subsequent targeted biopsy, with Az values of Receiver Operating Characteristic(ROC) curve was 0.83. The proposed CADx system showed reliable performance.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.11-19
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• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1272-1277
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• 2017

To assist radiologists for the characterization of breast masses, Computer-aided Diagnosis(CADx) system has been studied. The CADx system can improve the diagnostic accuracy of radiologists by providing objective information about breast masses. Morphological and texture features were extracted from the breast ultrasound images. Based on extracted features, the CADx system retrieves masses that are similar to a query mass from a reference library using a k-nearest neighbor (k-NN) approach. Eight similarity measures of distance, Euclidean, Chebyshev(Minkowski family), Canberra, Lorentzian($F_2$ family), Wave Hedges, Motyka(Intersection family), and Cosine, Dice(Inner Product family) are evaluated by ROC(Receiver Operating Characteristic) analysis. The Inner Product family measure used with the k-NN classifier provided slightly higher performance for classification of malignant and benign masses than those with the Minkowski, $F_2$, and Intersection family measures.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.34-43
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• 2010

Texture information plays an important role in object recognition and classification. To perform an accurate classification, the texture feature used in the classification must be highly discriminative. This paper presents a novel texture descriptor for texture-based image retrieval and its application in Computer-Aided Diagnosis (CAD) system for Emphysema classification. The texture descriptor is based on the combination of local surrounding neighborhood difference and centralized neighborhood difference and is named as Combined Neighborhood Difference (CND). The local differences of surrounding neighborhood difference and centralized neighborhood difference between pixels are compared and converted into binary codewords. Then binomial factor is assigned to the codewords in order to convert them into high discriminative unique values. The distribution of these unique values is computed and used as the texture feature vectors. The texture classification accuracies using Outex and Brodatz dataset show that CND achieves an average of 92.5%, whereas LBP, LND and Gabor filter achieve 89.3%, 90.7% and 83.6%, respectively. The implementations of CND in the computer-aided diagnosis of Emphysema is also presented in this paper.

• IE interfaces
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• v.21 no.4
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• pp.394-402
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• 2008

The objective of this paper is to design segmentation algorithm for applying the breast ultrasound image to CAD(Computer Aided Diagnosis). This study is conducted after understanding limits, used algorithm and demands of CAD system by interviewing with a medical doctor and analyzing related works based on a general CAD framework that is consisted of five step-establishment of plan, analysis of needs, design, implementation and test & maintenance. Detection function of CAD is accomplished by Canny algorithm and arithmetic operations for segmentation. In addition to, long computing time is solved by extracting ROI (Region Of Interests) and applying segmentation technical methods based morphology algorithm. Overall course of study is conducted by verification of medical doctor. And validity and verification are satisfied by medical doctor's confirmation. Moreover, manual segmentation of related works, restrictions on the number of tumor and dependency of image resolution etc. was solved. This study is utilized as a support system aided doctors' subjective diagnosis even though a lot of future studies is needed for entire application of CAD system.

• 한국기계연구소 소보
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• s.17
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• pp.61-68
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• 1987

The main objective of this paper is to develop the computer-aided vibrational signal processing and monitoring system of rotating machinery. This system has an automatic data acquisition capability and analyze for machine fault diagnosis. By spectrum analysis, machine’s failure can be identified. The monitoring system enables diagnosis of the fault in rotating machinery. In this study, the conventional electrical fans are selected as a model case. The date processing and fault monitoring system proposed here can be applied to the automation of the inspection process in assembling motor-shaft systems. The automatic inspection can enhance the product quality and keep it stable. Since the proposed system is developed for personal computers, it might be cheap in cost and easy in installation.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.319-322
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• 1997

This paper presents a CAD (Computer-Aided Diagnosis) system or detection of breast cancer, which is composed of personal computer, X-ray film scanner, high resolution display and application softwares. There are three major algorithms implemented in the application software. The irst algorithm is the adaptive enhancement of the digitized X-ray mammograms based on the first derivative and the local statistics. The second one is to detect the clustered microcalcifications by using the statistical texture analysis, and the third one is the classification of the clustered microcalcifications as malignant or benign by using the shape analysis. These algorithms were verified by real experiments.