Abstract #4283
Iterative Compressed Sensing Reconstruction Using Forward Model Based on MR Multi-Parameter
Jinseong Jang 1 , Tae-Joon Eo 1 , Narae Choi 1 , Minoh Kim 1 , Dongyeob Han 1 , Dong-Hyun Kim 1 , and Dosik Hwang 1
1
School of Electrical and Electronic
Engineering, Yonsei University, Seoul, Korea
Magnetic resonance fingerprinting is a method that can
quantitatively estimate MR parameters such as T1, T2 of
specific tissues, by matching pattern of signal
evolution obtained from the scanner with the pattern of
signal evolution that is generated from MR forward
modelling. the well-accepted Cartesian trajectory needs
to be considered for robust implementation of MRF for
fast processing In this study, efficient iterative
compressed sensing (CS) reconstruction method is
proposed to highly accelerate the Cartesian-trajectory
based acquisition for MRF, leading to the reduction
factor up to 16.
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