• Title/Summary/Keyword: Computer Aided Diagnosis

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Alzheimer's Disease Classification with Automated MRI Biomarker Detection Using Faster R-CNN for Alzheimer's Disease Diagnosis (치매 진단을 위한 Faster R-CNN 활용 MRI 바이오마커 자동 검출 연동 분류 기술 개발)

  • Son, Joo Hyung;Kim, Kyeong Tae;Choi, Jae Young
    • Journal of Korea Multimedia Society
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    • v.22 no.10
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    • pp.1168-1177
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    • 2019
  • In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.

Smart Device System for Strabismus Diagnosis (사시 진단을 위한 스마트 디바이스 시스템)

  • Yoon, Woong Bae;Oh, Ji Eun;Moon, Hyo Won;Yang, Hee Kyung;Hwang, Jeong Min;Park, Jong Il;Kim, Kwang Gi
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1538-1543
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    • 2016
  • Strabismus is a non-aligned state;the visual axis of each eye is not directed toward the same direction at the same time. Clinically, the degrees of strabismus are measured by prism cover test, corneal reflex test (Hirschberg test), prism reflex test (Krimsky prism test), But corneal reflex test and prism reflex test is a possibility that errors occur. we suggest a computer-aided diagnosis for strabismus. We made a mobile application to measure angles of strabismus. For 34 patients, we tested our application. The result of comparing between two methods, It showed a difference 7 Prism Diopter(PD). Our application gives strabismus angles just using a camera and a smart device. Therefore, it can reduce the cost and make the diagnosis of strabismus accurate.

Computer-Aided Diagnosis System for the Detection of Breast Cancer (유방암검출을 위한 컴퓨터 보조진단 시스템)

  • Lee, C.S.;Kim, J.K.;Park, H.W.
    • 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.

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Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman

  • Mirzal, Andri;Chaudhry, Shafique Ahmad
    • 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.

A Study on the Multi-View Based Computer Aided Diagnosis in Digital Mammography (디지털 유방영상에서 멀티영상 기반의 컴퓨터 보조 진단에 관한 연구)

  • Choi, Hyoung-Sik;Cho, Yong-Ho;Cho, Baek-Hwan;Moon, Woo-Kyoung;Im, Jung-Gi;Kim, In-Young;Kim, Sun-I.
    • Journal of Biomedical Engineering Research
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    • v.28 no.1
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    • pp.162-168
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    • 2007
  • For the past decade, the full-field digital mammography has been widely used for early diagnosis of breast cancer, and computer aided diagnosis has been developed to assist physicians as a second opinion. In this study, we try to predict the breast cancer using both mediolateral oblique(MLO) view and craniocaudal(CC) view together. A skilled radiologist selected 35 pairs of ROIs from both MLO view and CC view of digital mammogram. We extracted textural features using Spatial Grey Level Dependence matrix from each mammogram and evaluated the generalization performance of the classifier using Support Vector Machine. We compared the multi-view based classifier to single-view based classifier that is built from each mammogram view. The results represent that the multi-view based computer aided diagnosis in digital mammogram could improve the diagnostic performance and have good possibility for clinical use to assist physicians as a second opinion.

Computer Aided Diagnosis Applications for the Differential Diagnosis of Infarction: Apply on Brain CT Image (뇌경색 감별진단을 위한 컴퓨터보조진단 응용: Brain CT Images 적용)

  • Park, Hyong-Hu;Cho, Mun-Joo;Im, In-Chul;Lee, Jin-Soo
    • 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.

Use of the surface-based registration function of computer-aided design/computer-aided manufacturing software in medical simulation software for three-dimensional simulation of orthognathic surgery

  • Kang, Sang-Hoon;Lee, Jae-Won;Kim, Moon-Key
    • Journal of the Korean Association of Oral and Maxillofacial Surgeons
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    • v.39 no.4
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    • pp.197-199
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    • 2013
  • Three-dimensional (3D) computed tomography image models are helpful in reproducing the maxillofacial area; however, they do not necessarily provide an accurate representation of dental occlusion and the state of the teeth. Recent efforts have focused on improvement of dental imaging by replacement of computed tomography with other detailed digital images. Unfortunately, despite the advantages of medical simulation software in dentofacial analysis, diagnosis, and surgical simulation, it lacks adequate registration tools. Following up on our previous report on orthognathic simulation surgery using computer-aided design/computer-aided manufacturing (CAD/CAM) software, we recently used the registration functions of a CAD/CAM platform in conjunction with surgical simulation software. Therefore, we would like to introduce a new technique, which involves use of the registration functions of CAD/CAM software followed by transfer of the images into medical simulation software. This technique may be applicable when using various registration function tools from different software platforms.

Computer-Aided Vibration Signal Processing and Fault Monitoring System of Electrical-Fan Motors (컴퓨터를 이용한 선풍기모터의 진동신호처리 및 이상진단에 관한 연구)

  • Sin, Jung-Ho;Hwang, Gi-Hyeon;Choe, Yeong-Hyu;Park, Ju-Hyeok
    • 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.

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