Journal article
Improved model-based magnetic resonance spectroscopic imaging
IEEE transactions on medical imaging, Vol.26(10), pp.1305-1318
10/2007
DOI: 10.1109/TMI.2007.898583
PMID: 17948722
Abstract
Model-based techniques have the potential to reduce the artifacts and improve resolution in magnetic resonance spectroscopic imaging, without sacrificing the signal-to-noise ratio. However, the current approaches have a few drawbacks that limit their performance in practical applications. Specifically, the classical schemes use less flexible image models that lead to model misfit, thus resulting in artifacts. Moreover, the performance of the current approaches is negatively affected by the magnetic field inhomogeneity and spatial mismatch between the anatomical references and spectroscopic imaging data. In this paper, we propose efficient solutions to overcome these problems. We introduce a more flexible image model that represents the signal as a linear combination of compartmental and local basis functions. The former set represents the signal variations within the compartments, while the latter captures the local perturbations resulting from lesions or segmentation errors. Since the combined set is redundant, we obtain the reconstructions using sparsity penalized optimization. To compensate for the artifacts resulting from field inhomogeneity, we estimate the field map using alternate scans and use it in the reconstruction. We model the spatial mismatch as an affine transformation, whose parameters are estimated from the spectroscopy data.
Details
- Title: Subtitle
- Improved model-based magnetic resonance spectroscopic imaging
- Creators
- Mathews Jacob - Biomedical Engineering Department, University of Rochester, Rochester, NY 14622, USAXiaoping ZhuAndreas EbelNorbert SchuffZhi-Pei Liang
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.26(10), pp.1305-1318
- DOI
- 10.1109/TMI.2007.898583
- PMID
- 17948722
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers; United States
- Language
- English
- Date published
- 10/2007
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070881602771
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