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.
Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/2578 |
Date | 01 November 2005 |
Creators | Rane, Swati Dnyandeo |
Contributors | Ji, Jim X. |
Publisher | Texas A&M University |
Source Sets | Texas A and M University |
Language | en_US |
Detected Language | English |
Type | Book, Thesis, Electronic Thesis, text |
Format | 950695 bytes, electronic, application/pdf, born digital |
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