The motivation behind this research was to develop and investigate how effective a spatial-spatial-spectral algorithm, combining filtered-backprojection, variable-bandwidth and spatial-spectral imaging techniques would be in extracting spectral information from magnetic resonance images. The technique employed in this research, which combines the fore mentioned imaging techniques is believed to be original. It is known that the chemical shift artifact, in a magnetic resonance image becomes large as bandwidth decreases. A Ramlak filter and an inverse Radon transform was used to apply filtered-backprojection and spatial-spectral research to magnetic resonance imaging. The preliminary work in developing a spatial-spatial-spectral algorithm to extract spectral information from variable-bandwidth magnetic resonance images has been accomplished, but more work is needed to determine if this technique can successfully resolve metabolites. The effectiveness of this algorithm was found to depend on both the geometric complexity of the object, and the amount of resolution lost when an inverse Radon transform is applied to the image data. Both fat and water were found to be resolvable with this technique. In addition the CH2 and CH3 peaks were also found to be resolvable. It has been determined that this technique can resolve at least 25 Hz, but the highest possible resolution has yet to be determined.

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