Conference proceeding
Compartmentalized low-rank regularization with orthogonality constraints for high-resolution MRSI
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Vol.2016-, pp.960-963
04/2016
DOI: 10.1109/ISBI.2016.7493424
PMID: 33619440
Abstract
We introduce a novel compartmental low rank algorithm for high resolution MR spectroscopic imaging. We model the field inhomogeneity compensated MRSI dataset as the sum of a lipid dataset and a metabolite dataset using the spatial compartmental information obtained from water reference data. Both these datasets are modeled as low-rank subspaces, and are assumed to be orthogonal to each other. We formulate the recovery of the dataset from spiral measurements as a low-rank recovery problem. Experiments using numerical phantom and in-vivo data demonstrates the ability of the algorithm to provide improved spatial resolution and nuisance signal free spectra.
Details
- Title: Subtitle
- Compartmentalized low-rank regularization with orthogonality constraints for high-resolution MRSI
- Creators
- Ipshita Bhattacharya - Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USAMathews Jacob - Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
- Resource Type
- Conference proceeding
- Publication Details
- 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Vol.2016-, pp.960-963
- DOI
- 10.1109/ISBI.2016.7493424
- PMID
- 33619440
- NLM abbreviation
- Proc IEEE Int Symp Biomed Imaging
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Publisher
- IEEE
- Language
- English
- Date published
- 04/2016
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070465902771
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