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
Electronic and information engineering,
Korea University, Seongbuk-Gu, Seoul, Korea,
of Radiology, Soonchunhyang University Bucheon Hospital,
Department of Radiology, Ewha
Women's University Mokdong Hospital, Seoul, Korea,
of Radiology, The Catholic University of Korea St.
Mary's Hospital, Seoul, Korea,
Institute of Standards and Science, Daejeon, Korea,
Institute of Accreditation of Medical Imaging, Seoul,
MRI Team, Korea Basic Science Institute,
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.,
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