Conference proceeding
A blind compressive sensing frame work for accelerated dynamic MRI
2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.1060-1063
05/2012
DOI: 10.1109/ISBI.2012.6235741
PMCID: PMC3959993
PMID: 24663291
Abstract
We propose a novel blind compressive sensing (BCS) frame work to recover dynamic images from under-sampled measurements. This scheme models the the dynamic signal as a sparse linear combination of temporal basis functions, chosen from a large dictionary. The dictionary and the sparse coefficients are simultaneously estimated from the under-sampled measurements. Since the number of degrees of freedom of this model is much smaller than that of current low-rank methods, this scheme is expected to provide improved reconstructions for datasets with considerable inter-frame motion. We develop an efficient majorize-minimize algorithm to solve for the dynamic images. We use a continuation strategy to minimize the convergence of the algorithm to local minima. Numerical comparisons of the BCS scheme with low-rank methods demonstrate the significant improvement in performance in the presence of motion.
Details
- Title: Subtitle
- A blind compressive sensing frame work for accelerated dynamic MRI
- Creators
- Sajan Goud Lingala - Biomed. 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
- 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.1060-1063
- DOI
- 10.1109/ISBI.2012.6235741
- PMID
- 24663291
- PMCID
- PMC3959993
- NLM abbreviation
- Proc IEEE Int Symp Biomed Imaging
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Publisher
- IEEE
- Language
- English
- Date published
- 05/2012
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070595902771
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