Subspace based low rank & joint sparse matrix recovery

Sampurna Biswas; Sunrita Poddar; Soura Dasgupta; Raghuraman Mudumbai; Mathews Jacob

doi:10.1109/ACSSC.2014.7094525

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Conference proceeding

Subspace based low rank & joint sparse matrix recovery

Sampurna Biswas, Sunrita Poddar, Soura Dasgupta, Raghuraman Mudumbai and Mathews Jacob

2014 48th Asilomar Conference on Signals, Systems and Computers, Vol.2015-, pp.642-646

11/2014

DOI: 10.1109/ACSSC.2014.7094525

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Abstract

We consider the recovery of a low rank and jointly sparse matrix from under sampled measurements of its columns. This problem is highly relevant in the recovery of dynamic MRI data with high spatio-temporal resolution, where each column of the matrix corresponds to a frame in the image time series; the matrix is highly low-rank since the frames are highly correlated. Similarly the non-zero locations of the matrix in appropriate transform/frame domains (e.g. wavelet, gradient) are roughly the same in different frame. The superset of the support can be safely assumed to be jointly sparse. Unlike the classical multiple measurement vector (MMV) setup that measures all the snapshots using the same matrix, we consider each snapshot to be measured using a different measurement matrix. We show that this approach reduces the total number of measurements, especially when the rank of the matrix is much smaller than than its sparsity. Our experiments in the context of dynamic imaging shows that this approach is very useful in realizing free breathing cardiac MRI.

Magnetic resonance imaging

Subspace estimation

MMV

Joint sparsity

Sensors

Sparse matrices

Sparks

Joints

ADMM

MRI reconstruction

Image reconstruction

Details

Title: Subtitle: Subspace based low rank & joint sparse matrix recovery
Creators: Sampurna Biswas - Dept. of Electr. & Comput. Eng., Univ. Iowa, Iowa City, IA, USA
Sunrita Poddar - Dept. of Electr. & Comput. Eng., Univ. Iowa, Iowa City, IA, USA
Soura Dasgupta - Dept. of Electr. & Comput. Eng., Univ. Iowa, Iowa City, IA, USA
Raghuraman Mudumbai - Dept. of Electr. & Comput. Eng., Univ. Iowa, Iowa City, IA, USA
Mathews Jacob - Dept. of Electr. & Comput. Eng., Univ. Iowa, Iowa City, IA, USA
Resource Type: Conference proceeding
Publication Details: 2014 48th Asilomar Conference on Signals, Systems and Computers, Vol.2015-, pp.642-646
Publisher: IEEE
DOI: 10.1109/ACSSC.2014.7094525
ISSN: 1058-6393
eISSN: 2576-2303
Language: English
Date published: 11/2014
Academic Unit: Radiology; Electrical and Computer Engineering; Radiation Oncology; Iowa Neuroscience Institute; Roy J. Carver Department of Biomedical Engineering
Record Identifier: 9984070157102771

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