In Magnetic Resonance Imaging, the time required to generate an image is
proportional to the number of steps used to encode the spatial information. In rapid
imaging, an array of coil elements and receivers are used to reduce the number of
encoding steps required to generate an image. This is done using knowledge of the
spatial sensitivity of the array and receiver channels. Recently, these arrays have begun
to include a large number of coil elements. Ideally, each coil element would have its
own receiver channel to acquire the image data. In practice, this is not always possible
due to economic or other constraints. In this dissertation, methods are explored to
combine a large array to a limited number of receivers so as to optimize the performance
for parallel imaging; this dissertation focuses on SENSE in particular. Simple
combinations that represent larger coils that might be constructed are discussed. More
complex solutions form current sheets. One solution uses Roemer'ÃÂÃÂs method to optimize
image SNR at a set of points. In this dissertation, Roemer's solution is generalized to
give the weighting coefficients that optimize SNR over regions. Also, solutions fitted to
ideal profiles that minimize noise amplification are shown. These fitted profiles can
allow the SENSE algorithm to function at optimal reduction factors. Finally, a
description of how to build the combiner in hardware is discussed.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/5944 |
| Date | 17 September 2007 |
| Creators | Spence, Dan Kenrick |
| Contributors | Wright, Steven |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | 5169985 bytes, electronic, application/pdf, born digital |
Page generated in 0.0021 seconds