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Description:
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Magnetic Resonance Imaging (MRI ) is now increasingly being used for fast imaging
applications such as real -time cardiac imaging , functional brain imaging , contrast
enhanced MRI , etc . Imaging speed in MRI is mainly limited by different imaging
parameters selected by the pulse sequences , the subject being imaged and the RF
hardware system in operation . New pulse sequences have been developed in order to
decrease the imaging time by a faster k -space scan . However , they may not be fast
enough to facilitate imaging in real time . Parallel MRI (pMRI ) , a technique initially
used for improving image SNR , has emerged as an effective complementary approach
to reduce image scan -time . Five methods , viz . , SENSE [Pruesmann , 1999] , PILS
[Griswold , 2000] , SMASH [Sodickson , 1997] , GRAPPA [Griswold , 2002] and SPACE
RIP [Kyriakos , 2000] ; developed in the past decade have been studied , simulated
and compared in this research . Because of the dependence of the parallel imaging
methods on numerous factors such as receiver coil configuration , k -space subsampling
factor , k -space coverage in the imaging environment , there is a critical need to find
the method giving the best results under certain imaging conditions . The tools developed
in this research help the selection of the optimal method for parallel imaging
depending on a particular imaging environment and scanning parameters . Simulations
on real MR phased -array data show that SENSE and GRAPPA provide better
image reconstructions when compared to the remaining techniques . |