• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2375-2382
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• 2016

Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.475-481
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• 2005

현재 국내외에서는 유비쿼터스에 대한 연구 및 의료도메인에 대한 많은 연구가 진행되고 있다. 그러나 기존의 연구들은 전체적인 시스템에 대한 연구가 대부분이어서 실제 환경을 구축하는데 상당한 어려움이 따르고 있다. 본 연구에서는 위와 같은 문제점을 해결하기 위하여 고위험군 환자를 대상으로 다음과 같은 시나리오를 작성하였다. 시나리오는 Home -medical 서비스, Emergency call center 서비스 그리고 응급차량 서비스로 구성하였다. 본 연구에서는 위와 같은 시나리오를 기반으로 고위험군 환자의 생체 신호를 획득한 후 신경망을 이용하여 생체 신호 데이터를 학습한 후 환자의 이상 징후를 진단하는 CAD시스템의 프레임웍과 환자의 위험 수위를 단계별로 분류하는 알고리즘을 제시한다. 또한 과거의 데이터를 이용하여 미래의 환자상태를 예측하는 CAP시스템의 프레임웍을 제시하고 프레임웍에 대한 타당성을 검증하고자 한다.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.9-16
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• 2016

In this paper, we present a performance evaluation agent based on fuzzy cluster analysis and validity measures. The proposed agent is consists of three modules, fuzzy cluster analyzer, performance evaluation measures, and feature ranking algorithm for feature selection step in CAD system. Feature selection is an important step commonly used to create more accurate system to help human experts. Through this agent, we get the feature ranking on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. Also we design a CAD system incorporating the agent and apply five different feature combinations to the system. Experimental results proposed approach has higher classification accuracy and shows the feasibility as a diagnosis supporting tool.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.3
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• pp.201-208
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• 2007

Purpose: We investigated whether the diagnostic performance of SPECT scintimammography (SMM) can be improved by adding computer-aided diagnosis (CAD) of ultrasonography (US). Materials and methods: We reviewed breast SPECT SMM images and corresponding US images from 40 patients with breast masses (21 malignant and 19 benign tumors). The quantitative data of SPECT SMM were obtained as the uptake ratio of lesion to contralateral normal breast. The morphologic features of the breast lesions on US were extracted and quantitated using the automated CAD software program. The diagnostic performance of SPECT SMM and CAD of US alone was determined using receiver operating characteristic (ROC) curve analysis. The best discriminating parameter (D-value) combining SPECT SMM and the CAD of US was created. The sensitivity, specificity and accuracy of combined two diagnostic modalities were compared to those of a single one. Results: Both SPECT SMM and CAD of US showed a relatively good diagnostic performance (area under curve = 0.846 and 0.831, respectively). Combining the results of SPECT SMM and CAD of US resulted in improved diagnostic performance (area under curve =0.860), but there was no statistical differerence in sensitivity, specificity and accuracy between the combined method and a single modality. Conclusion: It seems that combining the results of SPECT SMM and CAD of breast US do not significantly improve the diagnostic performance for diagnosis of breast cancer, compared with that of SPECT SMM alone. However, SPECT SMM and CAD of US may complement each other in differential diagnosis of breast cancer.

• The Journal of Korean Academy of Prosthodontics
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• v.55 no.4
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• pp.410-418
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• 2017

Amelogenesis imperfecta characterized as abnormally formed enamel is caused by a defect of unique group of genes. Patients affected by this disease might have difficulties in social and psychological aspects due to non-esthetic teeth as well as functional problems caused by enamel detachment and tooth wear from their early ages. Adult patients with amelogenesis imperfecta can be treated with full-mouth restorations, which make functional and esthetic rehabilitations of severely worn tooth. However, the anterior open bite and lack of occlusal clearance for posterior teeth restorations due to compensatory extrusion are the intervening factors in the prosthetic treatment. Therefore, the determination of anterior tooth lengths, vertical dimension, and anterior guidance should be set carefully. Recently, computer-aided design and computer-aided manufacturing (CAD/CAM) techniques help systematic approaches and enable dentists to reduce time-consuming procedures in the diagnosis and treatment of full-mouth rehabilitation. This case report demonstrates the successful full mouth rehabilitation using a CAD/CAM system in a young adult patient with amelogenesis imperfecta and anterior open bite.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.1
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• pp.44-54
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• 2022

Without proper treatment on the multiple tooth missing area, the lack of posterior support and the supra-eruption of the teeth cause many severe complications of occlusion, vertical dimension and masticatory function. This report is a case of full-mouth rehabilitation of a patient with loss of posterior support and collapsed occlusion due to missing teeth area left untreated for a long time. The patient who is 68-year old male patient had some teeth fallen out while removing his old maxillary denture and was complaining about pain in the region of anterior teeth due to traumatic contact. The vertical dimension was corrected by 4 mm from the top cervical point of the canine through various evaluations and the edentulous area was treated with the implant fixed prostheses through computer guided implant surgery based on the diagnosis and treatment plan for definitive prostheses supported by computed tomography (CT) data analysis and CAD-CAM (Computer-aided design/computer-aided manufacturing) technique. After full mouth rehabilitation, the patient was very satisfied with remarkable improvements in mastication, function, and aesthetics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.68-80
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• 2013

Lung cancer is considered to be the leading cause of cancer death worldwide. A technique commonly used consists of analyzing sputum images for detecting lung cancer cells. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid errors. The manual screening of sputum samples has to be improved by using image processing techniques. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection and diagnosis of lung cancer based on the analysis of the sputum color image with the aim to attain a high accuracy rate and to reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a framework for segmentation and extraction of sputum cells in sputum images using respectively, a Bayesian classification method followed by region detection and feature extraction techniques to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer. We analyzed the performance of a Bayesian classification with respect to the color space representation and quantification. Our methods were validated via a series of experimentation conducted with a data set of 100 images. Our evaluation criteria were based on sensitivity, specificity and accuracy.

• Journal of Biomedical Engineering Research
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• v.26 no.5
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• pp.283-294
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• 2005

The Center for Imaging Human Structures (CIH) was established in December 2002 to develop new diagnostic imaging techniques and to make them available to the greater community of biomedical and clinical researchers at Sungkyunkwan University. CIH has been involved in 5 specific activities to provide solutions for early diagnosis and improved treatment of human diseases. The five area goals include: 1) development of a digital mammography system with computer aided diagnosis (CAD); 2) development of digital radiological imaging techniques; 3) development of unified medical solutions using 3D image fusion; 4) development of multi-purpose digital endoscopy; and, 5) evaluation of new imaging systems for clinical application

• Journal of KIISE:Software and Applications
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• v.35 no.8
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• pp.493-500
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• 2008

This paper proposes an electronic colon cleansing method using a patient CT profile for a virtual colonoscopy. The proposed method extracts the colon using cubic seeded region growing, and removes tagged materials adjacent to the colon. Residuals produced by a partial volume effect at the boundary of air-tagged material are deleted, and the removed soft tissue pixels due to a partial volume effect at the boundary of tagged material-soft tissue are recovered using a patient CT profile. The proposed method was applied to 16 virtual colonoscopy patient data sets, and produced promising results by a subjective evaluation of a radiologist and by a quantitative evaluation of a computer-aided diagnosis system.