Conference proceeding
Accelerated dynamic MRI using self expressiveness prior
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), Vol.2015-, pp.893-896
04/2015
DOI: 10.1109/ISBI.2015.7164014
Abstract
We introduce a self-expressiveness prior to exploit the redundancies between voxel profiles in dynamic MRI. Specifically, we express the temporal profile of each voxel in the dataset as a sparse linear combination of temporal profiles of other voxels. This scheme can be thought of as a direct approach to exploit the inter-voxel redundancies as opposed to low-rank and dictionary based schemes, which learn dictionaries from the data to represent the signal. The proposed representation may be interpreted as a union of subspaces model or as an analysis transform. The use of this algorithm is observed to considerably improve the recovery of myocardial perfusion MRI data from under sampled measurements.
Details
- Title: Subtitle
- Accelerated dynamic MRI using self expressiveness prior
- Creators
- Arvind Balachandrasekaran - Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USAMathews Jacob - Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
- Resource Type
- Conference proceeding
- Publication Details
- 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), Vol.2015-, pp.893-896
- Publisher
- IEEE
- DOI
- 10.1109/ISBI.2015.7164014
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Language
- English
- Date published
- 04/2015
- Academic Unit
- Electrical and Computer Engineering; Roy J. Carver Department of Biomedical Engineering; Radiology; Radiation Oncology; Iowa Neuroscience Institute
- Record Identifier
- 9984070711802771
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