Journal article
Deformation corrected compressed sensing (DC-CS): a novel framework for accelerated dynamic MRI
IEEE transactions on medical imaging, Vol.34(1), pp.72-85
01/2015
DOI: 10.1109/TMI.2014.2343953
PMCID: PMC4411243
PMID: 25095251
Abstract
We propose a novel deformation corrected compressed sensing (DC-CS) framework to recover contrast enhanced dynamic magnetic resonance images from undersampled measurements. We introduce a formulation that is capable of handling a wide class of sparsity/compactness priors on the deformation corrected dynamic signal. In this work, we consider example compactness priors such as sparsity in temporal Fourier domain, sparsity in temporal finite difference domain, and nuclear norm penalty to exploit low rank structure. Using variable splitting, we decouple the complex optimization problem to simpler and well understood sub problems; the resulting algorithm alternates between simple steps of shrinkage based denoising, deformable registration, and a quadratic optimization step. Additionally, we employ efficient continuation strategies to reduce the risk of convergence to local minima. The decoupling enabled by the proposed scheme enables us to apply this scheme to contrast enhanced MRI applications. Through experiments on numerical phantom and in vivo myocardial perfusion MRI datasets, we observe superior image quality of the proposed DC-CS scheme in comparison to the classical k-t FOCUSS with motion estimation/correction scheme, and demonstrate reduced motion artifacts over classical compressed sensing schemes that utilize the compact priors on the original deformation uncorrected signal.
Details
- Title: Subtitle
- Deformation corrected compressed sensing (DC-CS): a novel framework for accelerated dynamic MRI
- Creators
- Sajan Goud Lingala - Department of Biomedical Engineering, The University of Iowa, IA, USAEdward DiBella - Department of Radiology, University of Utah, Utah, USAMathews Jacob - Department of Electrical and Computer Engineering, The University of Iowa, IA, USA
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.34(1), pp.72-85
- DOI
- 10.1109/TMI.2014.2343953
- PMID
- 25095251
- PMCID
- PMC4411243
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers
- Grant note
- name: (NSF), award: CCF-0844812, CCF-1116067, 1R21HL109710-01A1, 12 PRE11920052
- Language
- English
- Date published
- 01/2015
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070949002771
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