Image reconstruction from sparse data samples in MRI accounting for phase roll

Samuel J. LaRoque; Emil Y. Sidky; Gregory S. Karczmar; Xiaochuan Pan

doi:10.1117/12.769568

18 March 2008 Image reconstruction from sparse data samples in MRI accounting for phase roll

Samuel J. LaRoque, Emil Y. Sidky, Gregory S. Karczmar, Xiaochuan Pan

Proceedings Volume 6913, Medical Imaging 2008: Physics of Medical Imaging; 69130E (2008) https://doi.org/10.1117/12.769568
Event: Medical Imaging, 2008, San Diego, California, United States

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.

Citation Download Citation

Samuel J. LaRoque, Emil Y. Sidky, Gregory S. Karczmar, and Xiaochuan Pan "Image reconstruction from sparse data samples in MRI accounting for phase roll", Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69130E (18 March 2008); https://doi.org/10.1117/12.769568

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