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Abstract #1853

Quantitative MR System Evaluation Using the KRMP-4 Phantom - Comparison with the ACR Phantom

Jong-Min Kim 1 , Jang-Gyu Cha 2 , Ji-Young Hwang 3 , Seung-Eun Jung 4 , Hyunn-Kyoon Lim 5 , Do-wan Kim 6 , Kwang-Su Kim 6 , Sung-Jin Kang 2 , Han-Joong Kim 1 , Suchit Kumar 1 , Junyong Park 7 , Chulhyun Lee 7 , and Chang-Hyun Oh 1

1 Electronic and information engineering, Korea University, Seongbuk-Gu, Seoul, Korea, 2 Department of Radiology, Soonchunhyang University Bucheon Hospital, Seoul, Korea, 3 Department of Radiology, Ewha Women's University Mokdong Hospital, Seoul, Korea, 4 Department of Radiology, The Catholic University of Korea St. Mary's Hospital, Seoul, Korea, 5 Korea Research Institute of Standards and Science, Daejeon, Korea, 6 Korean Institute of Accreditation of Medical Imaging, Seoul, Korea, 7 The MRI Team, Korea Basic Science Institute, Chungcheongbuk-do, Korea

The quality evaluation schemes such as the ACR methods1 are good enough to decide whether the MRI system is useful for clinical application based on certain measurement parameters showing the image quality. In ACR method, 11 slices of MR images are usually acquired on the ACR phantom and they are used to evaluate the 7 items (geometric accuracy, high-contrast spatial resolution, slice thickness accuracy, slice position accuracy, image intensity uniformity, percent-signal ghosting, and low-contrast object detectability). However, there are several limitations of ACR method like observer-dependent, time consuming, and accurate numerical ratings on the system performance. In this study, 3 items (vessel conspicuity, brain tissue contrast, SNR) in addition to ACR method is proposed. For semi-automatic and quantitative MR system classification, all of above-mentioned items are evaluated numerically by using MATLAB (Mathwork, Inc., MA).

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