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Proceedings Paper

Image reconstruction from sparse data samples in MRI accounting for phase roll
Author(s): Samuel J. LaRoque; Emil Y. Sidky; Gregory S. Karczmar; Xiaochuan Pan
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Paper Abstract

In this study we apply a total variation (TV) minimization algorithm to image reconstruction in magnetic resonance imaging (MRI). This algorithm is particularly effective for underlying images that are approximately piecewise constant. While the underlying proton spin density in MRI can satisfy this condition under certain circumstances, it is often distorted by unavoidable physical factors that alter the phase of the complex image. In this work, we employ a known method of removing this slow phase variation resulting from magnetic field inhomogeneities to obtain a spin density distribution that is piecewise constant. After the phase removal, we apply the TV minimization algorithm to obtain images from 20% of the full MRI data set.

Paper Details

Date Published: 18 March 2008
PDF: 6 pages
Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69130E (18 March 2008); doi: 10.1117/12.769568
Show Author Affiliations
Samuel J. LaRoque, The Univ. of Chicago (United States)
Emil Y. Sidky, The Univ. of Chicago (United States)
Gregory S. Karczmar, The Univ. of Chicago (United States)
Xiaochuan Pan, The Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 6913:
Medical Imaging 2008: Physics of Medical Imaging
Jiang Hsieh; Ehsan Samei, Editor(s)

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