Conference proceeding
Accelerated dynamic MRI using structured low rank matrix completion
2016 IEEE International Conference on Image Processing (ICIP), Vol.2016-, pp.1858-1862
09/2016
DOI: 10.1109/ICIP.2016.7532680
PMID: 33597830
Abstract
We introduce a fast structured low-rank matrix completion algorithm with low memory & computational demand to recover the dynamic MRI data from undersampled measurements. The 3-D dataset is modeled as a piecewise smooth signal, whose discontinuities are localized to the zero sets of a bandlimited function. We show that a structured matrix corresponding to convolution with the Fourier coefficients of the signal derivatives is highly low-rank. This property enables us to recover the signal from undersampled measurements. The application of this scheme in dynamic MRI shows significant improvement over state of the art methods.
Details
- Title: Subtitle
- Accelerated dynamic MRI using structured low rank matrix completion
- Creators
- Arvind Balachandrasekaran - Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USAGreg Ongie - Dept. of Math., 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 International Conference on Image Processing (ICIP), Vol.2016-, pp.1858-1862
- DOI
- 10.1109/ICIP.2016.7532680
- PMID
- 33597830
- NLM abbreviation
- Proc Int Conf Image Proc
- ISSN
- 1522-4880
- eISSN
- 2381-8549
- Publisher
- IEEE
- Language
- English
- Date published
- 09/2016
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070637902771
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