Accelerated whole-brain multi-parameter mapping using blind compressed sensing

Sampada Bhave; Sajan Goud Lingala; Casey P Johnson; Vincent A Magnotta; Mathews Jacob

doi:10.1002/mrm.25722

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Accelerated whole-brain multi-parameter mapping using blind compressed sensing

Journal article

Open access

Peer reviewed

Accelerated whole-brain multi-parameter mapping using blind compressed sensing

Sampada Bhave, Sajan Goud Lingala, Casey P Johnson, Vincent A Magnotta and Mathews Jacob

Magnetic resonance in medicine, Vol.75(3), pp.1175-1186

03/2016

DOI: 10.1002/mrm.25722

PMCID: PMC4598248

PMID: 25850952

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https://doi.org/10.1002/mrm.25722View

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Abstract

To introduce a blind compressed sensing (BCS) framework to accelerate multi-parameter MR mapping, and demonstrate its feasibility in high-resolution, whole-brain T1ρ and T2 mapping.\nBCS models the evolution of magnetization at every pixel as a sparse linear combination of bases in a dictionary. Unlike compressed sensing, the dictionary and the sparse coefficients are jointly estimated from undersampled data. Large number of non-orthogonal bases in BCS accounts for more complex signals than low rank representations. The low degree of freedom of BCS, attributed to sparse coefficients, translates to fewer artifacts at high acceleration factors (R).\nFrom 2D retrospective undersampling experiments, the mean square errors in T1ρ and T2 maps were observed to be within 0.1% up to R = 10. BCS was observed to be more robust to patient-specific motion as compared to other compressed sensing schemes and resulted in minimal degradation of parameter maps in the presence of motion. Our results suggested that BCS can provide an acceleration factor of 8 in prospective 3D imaging with reasonable reconstructions.\nBCS considerably reduces scan time for multiparameter mapping of the whole brain with minimal artifacts, and is more robust to motion-induced signal changes compared to current compressed sensing and principal component analysis-based techniques.

Brain - diagnostic imaging

Reproducibility of Results

Algorithms

Humans

Imaging, Three-Dimensional - methods

Magnetic Resonance Imaging - methods

Brain Mapping - methods

Details

Title: Subtitle: Accelerated whole-brain multi-parameter mapping using blind compressed sensing
Creators: Sampada Bhave - Department of Electrical and Computer Engineering, The University of Iowa, Iowa, USA
Sajan Goud Lingala - Department of Electrical Engineering, University of Southern California, California, USA
Casey P Johnson - Department of Radiology, The University of Iowa, Iowa, USA
Vincent A Magnotta - Department of Radiology, The University of Iowa, Iowa, USA
Mathews Jacob - Department of Electrical and Computer Engineering, The University of Iowa, Iowa, USA
Resource Type: Journal article
Publication Details: Magnetic resonance in medicine, Vol.75(3), pp.1175-1186
DOI: 10.1002/mrm.25722
PMID: 25850952
PMCID: PMC4598248
NLM abbreviation: Magn Reson Med
ISSN: 0740-3194
eISSN: 1522-2594
Publisher: United States
Grant note: NIH 1R21HL109710-01A1 / NHLBI NIH HHS\nR21 HL109710 / NHLBI NIH HHS
Language: English
Date published: 03/2016
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Psychiatry; Iowa Neuroscience Institute; Radiation Oncology
Record Identifier: 9984066385302771

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