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Cerebral blood flow measurement by dynamic contrast MRI using singular value decomposition with an adaptive threshold
Author(s) -
Liu HoLing,
Pu Yonglin,
Liu Yijun,
Nickerson Lisa,
Andrews Trevor,
Fox Peter T.,
Gao JiaHong
Publication year - 1999
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/(sici)1522-2594(199907)42:1<167::aid-mrm22>3.0.co;2-q
Subject(s) - singular value decomposition , deconvolution , thresholding , cerebral blood flow , blood flow , nuclear magnetic resonance , threshold limit value , magnetic resonance imaging , mathematics , nuclear medicine , biomedical engineering , computer science , algorithm , physics , artificial intelligence , chemistry , medicine , radiology , organic chemistry , cardiology , image (mathematics)
Singular value decomposition (SVD) is a promising deconvolution technique for use in dynamic contrast agent magnetic resonance perfusion imaging. Computer simulations, however, show that the selection of the threshold for SVD affects the accuracy of the cerebral blood flow measurements and may distort the shape of the vascular residue function. In this report, a pixel‐by‐pixel thresholding method is proposed based on the signal‐to‐noise ratio of the concentration time curve at maximum concentration (SNR C ). Monte Carlo simulations were used to determine the optimal threshold for different SNR C . This technique was used to analyze data from six healthy volunteers, resulting in a mean gray to white matter cerebral blood flow ratio of 2.67 ± 0.07. This value is in excellent agreement with values published in the literature. Magn Reson Med 42:167–172, 1999. © 1999 Wiley‐Liss, Inc.