Robust Reconstruction of MRSI Data Using a Sparse Spectral Model and High Resolution MRI Priors

Ramin Eslami; Mathews Jacob

doi:10.1109/TMI.2010.2046673

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Robust Reconstruction of MRSI Data Using a Sparse Spectral Model and High Resolution MRI Priors

Journal article

Peer reviewed

Robust Reconstruction of MRSI Data Using a Sparse Spectral Model and High Resolution MRI Priors

Ramin Eslami and Mathews Jacob

IEEE transactions on medical imaging, Vol.29(6), pp.1297-1309

06/2010

DOI: 10.1109/TMI.2010.2046673

PMID: 20363676

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Abstract

We introduce a novel algorithm to address the challenges in magnetic resonance (MR) spectroscopic imaging. In contrast to classical sequential data processing schemes, the proposed method combines the reconstruction and postprocessing steps into a unified algorithm. This integrated approach enables us to inject a range of prior information into the data processing scheme, thus constraining the reconstructions. We use high resolution, 3-D estimate of the magnetic field inhomogeneity map to generate an accurate forward model, while a high resolution estimate of the fat/water boundary is used to minimize spectral leakage artifacts. We parameterize the spectrum at each voxel as a sparse linear combination of spikes and polynomials to capture the metabolite and baseline components, respectively. The constrained model makes the problem better conditioned in regions with significant field inhomogeneity, thus enabling the recovery even in regions with high field map variations. To exploit the high resolution MR information, we formulate the problem as an anatomically constrained total variation optimization scheme on a grid with the same spacing as the magnetic resonance imaging data. We analyze the performance of the proposed scheme using phantom and human subjects. Quantitative and qualitative comparisons indicate a significant improvement in spectral quality and lower leakage artifacts.

magnetic resonance spectroscopic imaging (MRSI)

Spectroscopy

Image resolution

B_{0} inhomogeneity compensation

Magnetic resonance

High-resolution imaging

field map

Data processing

sparsity

fat leakage

Image reconstruction

Magnetic resonance imaging

ell _{1} -minimization

Robustness

Polynomials

total variation

Magnetic fields

Details

Title: Subtitle: Robust Reconstruction of MRSI Data Using a Sparse Spectral Model and High Resolution MRI Priors
Creators: Ramin Eslami - Dept. of Biomed. Eng., Univ. of Rochester, Rochester, NY, USA
Mathews Jacob - Dept. of Biomed. Eng., Univ. of Rochester, Rochester, NY, USA
Resource Type: Journal article
Publication Details: IEEE transactions on medical imaging, Vol.29(6), pp.1297-1309
DOI: 10.1109/TMI.2010.2046673
PMID: 20363676
NLM abbreviation: IEEE Trans Med Imaging
ISSN: 0278-0062
eISSN: 1558-254X
Publisher: Institute of Electrical and Electronics Engineers
Language: English
Date published: 06/2010
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
Record Identifier: 9984070853702771

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