• Title/Summary/Keyword: 의료 이미지 판독

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Development of High Resolution Iris Camera Module using IoT Device (IoT 디바이스를 활용한 고해상도 홍채 카메라 모듈 개발)

  • Seo, Jin-beom;Cho, Young-bok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.3
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    • pp.371-377
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    • 2020
  • Currently used iris cameras are expensive and have many limitations in their use. Existing iris cameras are inconvenient in interworking with newly developed software, and light reflections generated during iris photography are inadequate for medical use. Therefore, it is impossible to utilize the existing camera to take an image by yourself. In this paper, the iris camera is newly constructed so that the iris can be photographed by ourselves and the area of interest can be seen well. Anyone can easily wear glasses-type iris cameras to acquire images using IoT devices, and the acquired images are linked to the iris analysis program and used to read genetic weak parts. The proposed iris camera module automatically provides light reflection, shake, and accurate focus when capturing images, increasing the accuracy of image analysis to 91.49%. In addition, we have proved through experiments that one image processing time is fast as 0.007ms due to accurate image input.

Optical Design for High Brightness Direct Type Backlight Unit Using Medical LCD Application (의료용 초고휘도 LCD 소자를 위한 직하형 Backlight의 최적설계)

  • Han, Jeong-Min;Kim, Won-Bae
    • Journal of Satellite, Information and Communications
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    • v.11 no.3
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    • pp.28-31
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    • 2016
  • In this study, it was investigated about optical simulation in highg brightness and high uniformity direct-type backlight design for medical application. Direct-type backlight has been used high-brightness backlight such as Medical LCD application. The key parameter in designing direct-type backlight was consists of three geometrical dimension such as the distance of two lamps, the gap of lamp and reflection plate and the number of lamps. It has many of variations in optical design and it causes the different properties in backlight system. It shows the best values of above parameters; 26mm of the distance of two lamps, 4.5mm of the gap of lamp and reflection plate and 16 lamps. And we produced the specimen as above condition, and acquired good result in backlight such as the value of the brightness is 6423 nit in center of emission area and less than 5% in brightness uniformity. It shows the effective ways of designing backlight system using optical simulation method for medical LCD application.

Development of Hospital Image Management and Communication System (의료용 화상정보 처리 시스템 개발)

  • 이준하;이상학;신현진
    • Progress in Medical Physics
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    • v.4 no.2
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    • pp.59-67
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    • 1993
  • In this paper, we present a result of our study on how to construct a HIMCS(hospital image management and communication system) based on Windows system. The proposed HIMCS is composed of image acquisition units, image archiving and processing units, display units, and all units are interfaced with LAN. We construct high speed image transmission system for distributed database and retrieval of various medical pictures in ward through image transmission system and realize integrated image diagnosis. Hospital image management and communication systems(HIMCS) have been proposed as a way to meet the challenge presented by the growing volume of medical imaging data. These systems are based on the concept of handing images in digital form, there by marking use of advances in computer-based technology. A HIMCS offers a wide spectrum of advantages over filmbased imaging. Digital acquisition of images eliminates the need for film processing and associated costs in both time and materials.

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A Study on a Mask R-CNN-Based Diagnostic System Measuring DDH Angles on Ultrasound Scans (다중 트레이닝 기법을 이용한 MASK R-CNN의 초음파 DDH 각도 측정 진단 시스템 연구)

  • Hwang, Seok-Min;Lee, Si-Wook;Lee, Jong-Ha
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.4
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    • pp.183-194
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    • 2020
  • Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 x 10e-4. Training was stopped when the validation loss was at the minimum. respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room

Analysis Study on the Detection and Classification of COVID-19 in Chest X-ray Images using Artificial Intelligence (인공지능을 활용한 흉부 엑스선 영상의 코로나19 검출 및 분류에 대한 분석 연구)

  • Yoon, Myeong-Seong;Kwon, Chae-Rim;Kim, Sung-Min;Kim, Su-In;Jo, Sung-Jun;Choi, Yu-Chan;Kim, Sang-Hyun
    • Journal of the Korean Society of Radiology
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    • v.16 no.5
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    • pp.661-672
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    • 2022
  • After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.

Improved Anatomical Landmark Detection Using Attention Modules and Geometric Data Augmentation in X-ray Images (어텐션 모듈과 기하학적 데이터 증강을 통한 X-ray 영상 내 해부학적 랜드마크 검출 성능 향상)

  • Lee, Hyo-Jeong;Ma, Se-Rie;Choi, Jang-Hwan
    • Journal of the Korea Computer Graphics Society
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    • v.28 no.3
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    • pp.55-65
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    • 2022
  • Recently, deep learning-based automated systems for identifying and detecting landmarks have been proposed. In order to train such a deep learning-based model without overfitting, a large amount of image and labeling data is required. Conventionally, an experienced reader manually identifies and labels landmarks in a patient's image. However, such measurement is not only expensive, but also has poor reproducibility, so the need for an automated labeling method has been raised. In addition, in the X-ray image, since various human tissues on the path through which the photons pass are displayed, it is difficult to identify the landmark compared to a general natural image or a 3D image modality image. In this study, we propose a geometric data augmentation technique that enables the generation of a large amount of labeling data in X-ray images. In addition, the optimal attention mechanism for landmark detection was presented through the implementation and application of various attention techniques to improve the detection performance of 16 major landmarks in the skull. Finally, among the major cranial landmarks, markers that ensure stable detection are derived, and these markers are expected to have high clinical application potential.

Computed Tomography of the Left Atrium and Left Atrial Appendage: A Pictorial Essay on the Anatomy, Normal Variants, and Pathology (좌심방과 좌심방이의 전산화단층촬영 소견: 해부학, 정상변이 및 질환에 관한 임상화보 )

  • Minji Song; Sung Jin Kim;Hyun Jung Koo;Moon Young Kim;Jin Young Yoo
    • Journal of the Korean Society of Radiology
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    • v.81 no.2
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    • pp.272-289
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    • 2020
  • Current advances in CT techniques allow thorough evaluation of the beating heart. The strengths of cardiac CT relative to echocardiography and magnetic resonance imaging are its high availability in most institutions, rapid production of high-quality images, and outstanding delineation of the anatomy. For many normal variants and pathologic conditions, such as thrombi, masses, and congenital abnormalities of the left atrium, CT findings are sufficient to make a presumptive diagnosis. Assessments of the left atrium and left atrial appendage are particularly important for the management of atrial fibrillation, as various catheter-based procedures are aimed at the mechanical and electrical isolation of these structures. CT offers information crucial to a successful catheter-based procedure or surgery. Therefore, a comprehensive review of the geometry (shape, size, and relative position), along with various CT imaging features of pathologic states, should be provided in radiology reports to be of clinical value.