• Title/Summary/Keyword: 의료영상 분석

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A Study for Effects of Image Quality due to Scatter Ray produced by Increasing of Tube Voltage (관전압 증가에 기인한 산란선 발생의 화질 영향 연구)

  • Park, Ji-Koon;Jun, Je-Hoon;Yang, Sung-Woo;Kim, Kyo-Tae;Choi, Il-Hong;Kang, Sang-Sik
    • Journal of the Korean Society of Radiology
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    • v.11 no.7
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    • pp.663-669
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    • 2017
  • In diagnostic medical imaging, it is essential to reduce the scattered radiation for the high medical image quality and low patient dose. Therefore, in this study, the influence of the scattered radiation on medical images was analyzed as the tube voltage increases. For this purpose, ANSI chest phantom was used to measure the scattering ratio, and the scattering effect on the image quality was investigated by RMS evaluation, RSD and NPS analysis. It was found that the scattering ratio with increasing x-ray tube voltage gradually increased to 48.8% at 73 kV tube voltage and to 80.1% at 93 kV tube voltage. As a result of RMS analysis for evaluating the image quality, RMS value according to increase of tube voltage was increased, resulting in low image quality. Also, the NPS value at 2.5 lp/mm spatial frequency was increased by 20% when the tube voltage was increased by 93 kV compared to the tube voltage of 73 kV. From this study, it can be seen that the scattering radiation have a significant effect on the image quality according to the increase of x-ray tube voltage. The results of this study can be used as basic data for the improvement of medical imaging quality.

Feature Extraction by Line-clustering Segmentation Method (선군집분할방법에 의한 특징 추출)

  • Hwang Jae-Ho
    • The KIPS Transactions:PartB
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    • v.13B no.4 s.107
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    • pp.401-408
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    • 2006
  • In this paper, we propose a new class of segmentation technique for feature extraction based on the statistical and regional classification at each vertical or horizontal line of digital image data. Data is processed and clustered at each line, different from the point or space process. They are designed to segment gray-scale sectional images using a horizontal and vertical line process due to their statistical and property differences, and to extract the feature. The techniques presented here show efficient results in case of the gray level overlap and not having threshold image. Such images are also not easy to be segmented by the global or local threshold methods. Line pixels inform us the sectionable data, and can be set according to cluster quality due to the differences of histogram and statistical data. The total segmentation on line clusters can be obtained by adaptive extension onto the horizontal axis. Each processed region has its own pixel value, resulting in feature extraction. The advantage and effectiveness of the line-cluster approach are both shown theoretically and demonstrated through the region-segmental carotid artery medical image processing.

A Boundary Extraction Method Based on Active Contour Model and Dynamic Programming (능동 윤곽선 모델을 이용한 경계선 추출과 다이나믹 프로그래밍)

  • 김령주;김영철;최흥국
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05c
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    • pp.282-285
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    • 2002
  • 의료영상에서 윤곽선의 추출은 관심영역 대한 객관적인 수치 즉 면적, 부피, 장단축의 길이 등을 분석하고 3차원 재구성을 위해 선행되어야 하는 중요한 과정이다. 현재 윤곽선 추출에 대한 않은 방법들이 개발 중에 있으나 이 방법들은 한계를 지니고 있어 더 높은 수준의 처리가 요구된다. 본 논문에서는 active contour model(snake)을 이용하여 MR뇌 영상에서 종양을 추출하였다. Snake의 에너지 최적화 문제를 dynamic programming을 사용하여 개선하였으며 canny edge detection을 이용하여 잡음에 덜 민감하도록 하였다.

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Leision Detection in Chest X-ray Images based on Coreset of Patch Feature (패치 특징 코어세트 기반의 흉부 X-Ray 영상에서의 병변 유무 감지)

  • Kim, Hyun-bin;Chun, Jun-Chul
    • Journal of Internet Computing and Services
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    • v.23 no.3
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    • pp.35-45
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    • 2022
  • Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

Segmentation of Lung and Lung Lobes in EBT Medical Images (EBT 의료 영상에서 폐 영역 추출 및 폐엽 분할)

  • 김영희;이성기
    • Journal of KIISE:Software and Applications
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    • v.31 no.3
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    • pp.276-292
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    • 2004
  • In this paper. we present methods that extract lung regions from chest EBT(electron beam tomography) images then segment the extracted lung region into lung lobes. We use histogram based thresholding and mathematical morphology for extracting lung regions. For detecting pulmonary fissures, we use edge detector and knowledge-based search method. We suggest this edge detector, which uses adaptive filter scale, to work very well for real edge and insensitive for edge by noise. Our experiments showed about 95% accuracy or higher in extracting lung regions and about 5 pixel distance error in detecting pulmonary fissures.

Efficient Multi-Disease Diagnosis in AI Medical Imaging Through Minimal Preprocessing Without Segmentation Labeling (세그멘테이션 라벨링 없는 최소 전처리를 통한 AI 의료 영상에서의 다 질병 진단 효율화)

  • Dong-Jun Seo;Seung-Chan Lee;Yoon-Jung Heo;Il-Yong Won
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.424-425
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    • 2023
  • AI 의료 영상 분석 기술은 의료 분야의 인력 부족 문제를 해결하는 방법으로 주목받고 있다. 이전 연구들은 세그멘테이션 라벨링과 질병 유무를 결합하여 판단하는데, 이 방법은 큰 비용과 시간이 소요된다. 본 논문은 의료 전문가의 세그멘테이션 라벨링 없이 병명 라벨만의 학습으로 질병을 어느 정도 진단할 수 있음을 보인다. 실험에 따르면 의미있는 결과를 확인할 수 있었다.

Accelerating Medical Image Processing on Integrated GPU Using OpenCL (OpenCL을 이용한 내장형 GPU에서의 의학영상처리 가속화)

  • Kim, Beom-Jun;Shin, Byeong-seok
    • Journal of the Korea Computer Graphics Society
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    • v.23 no.2
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    • pp.1-10
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    • 2017
  • A variety of filters are applied to improve the quality of noise and low resolution medical images. This is necessary to reduce the radiation dose of the patient and to improve the utilization of the conventional spherical imaging equipment. In the conventional method, it is common to perform filtering using the CPU of the PC. However, it is difficult to produce results in real time by applying various calculations and filters to high-resolution human images using only the CPU performance of a PC used in a hospital. In this paper, we analyze the structure and performance of Intel integrated GPU in CPU and propose a method to perform image filtering using OpenCL parallel processing function. By applying complex filters with high computational complexity to medical images, high quality images can be generated in real time.

A Study of Image Characteristics due to Focus-Grid and Head Phantom Decentering from the Armorphos Silicon Thin Film Transistor Detector the Fixed Focus-Grid is Applied (고정식 초점형 격자가 적용된 비정절 실리콘 평판형 검출기에서 초점-격자와 두부 팬텀의 중심 변위에 의한 화질 특성에 관한 연구)

  • Choi, Jun-Gu;Kim, Byeong-Gi;Cha, Seon-Hwa;Kim, Gyeong-Su
    • Korean Journal of Digital Imaging in Medicine
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    • v.9 no.1
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    • pp.7-15
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    • 2007
  • This study aim to investigate image characteristics due to focus-grid and head phantom decentering from the armorphos silicon thin film transistor detector the fixed focus-grid is applied, wish to propose right use method of digital medical equipment. Acquired image according to focus-grid and head phantom position decentering using head phantom on armorphos silicon thin film transistor detector the fixed focus-grid is applied. acquired image evaluate pixel value, histogram, plot profile, surface plot using NIB (Image J) image analysis program and compared decentering image with standard image. Mean value and standard deviation value of focus-grid lateral decentering and duplex decentering of focus-grid and head phantom decreased by ratio, consequently increase of horizontality, diagonal decentering. also, deteriorated contrast of image because frequency of high pixel value decreases fairly. according increases decentering, image distortion phenomenon was increase, by next time, pixel mean value of head phantom decentering was no big change but horizontality, diagonal, mean value and standard deviation value of pixel decreased by ratio. Even if increase pixel noise of image because wide latitude and post processing ability of digital detector, radiotechnologist can not recognize. Therefore, radiotechnologist must recognize correctly the photographing factors which increases pixel noise on the grid system installation digital detector and should exam.

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Design and Analysis of Hospital Management Agent in PDA Environment (PDA 환경에서의 병원관리 Agent의 분석 및 설계)

  • Lee, Hyoung-Sunk;Jung, Sung-Hoon;Kim, Chang-Su;Yim, Jae-Hong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05b
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    • pp.787-790
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    • 2003
  • 통신기술과 의료장비의 발달은 환자에 대한 의료혜택의 기회를 확대하고, 최상의 의료서비스를 제공하려는 병원들에 있어서 전산 시스템은 빼놓을 수 없는 병원내 주요 기반시설로서 등장하게 되었다. 멀티미디어 기술과 정보통신의 발달은 의료분야의 정보화 및 자동화 기술 발전에 커다란 영향을 주어 의료 영상 및 각종 의료정보를 고속의 네트워킹 올 통해 전송할 수 있는 PACS(Picture Archiving and Communications System)의 개발을 가능하게 하였다. 본 논문에서는 무선네트워크의 발달과 PDA(Personal Digital Assistants)의 보편화에 따라 PDA를 이용하여 HIS(Hospital Information System)/RIS(Radiology Information System)/PACS의 자료를 검색 및 갱신할 수 있도록 설계하고, 현재 병원의 데이터베이스와 PDA의 연동이 가능하도록 병원관리 에이전트를 분석 및 설계하였다.

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Evaluating the Usefulness of Diagnosis through 3D Printing Technology (3D프린팅 기술을 이용한 심혈관 질환 진단의 유용성 평가)

  • Park, Chun-Kyu;Kim, Jung-Hun
    • Journal of the Korean Society of Radiology
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    • v.15 no.5
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    • pp.691-696
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    • 2021
  • In order to prevent and treat a patient's disease, the anatomical structure of the lesion through medical imaging is one of the important processes. However, there is a limit to the image displayed on the screen, so many studies are underway to overcome this by using 3D printing technology. To this end, this study implemented a three-dimensional cardiovascular model using actual patient image data, printed it out using a 3D printer, and conducted a usefulness test on current medical professionals. As a result of the usefulness evaluation, when the questionnaire conducted by a total of 5 people was converted to the Likert scale, the average value of all items showed a high result of 4.83 points, and the result of the cross-analysis was (P) = 10.000 (0.265), which was equally positive among all the questionnaires survey results were presented. Based on the results, it is expected that 3D printing technology will help advance medical technology.