Dictionary learning for compressive parameter mapping in magnetic resonance imaging

Benjamin P. Berman; Mahesh B. Keerthivasan; Zhitao Li; Diego R. Martin; Maria I. Altbach; Ali Bilgin

doi:10.1117/12.2187088

Dictionary learning for compressive parameter mapping in magnetic resonance imaging

Benjamin P. Berman, Mahesh B. Keerthivasan, Zhitao Li, Diego R. Martin, Maria I. Altbach, Ali Bilgin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Parameter mapping is a valuable quantitative tool for soft tissue contrast. Accelerated data acquisition is critical for clinical utility, which has lead to various novel reconstruction techniques. In this work, a model-based compressed sensing method is extended to include a sparse regularization that is learned from the principal component coefficient. The principal components for a range of T² decay curves are computed, and the coefficients of the principal components are reconstructed. These coefficient maps share coherent spatial structures, suggesting a patch{based dictionary is a well suited sparse transformation. This transformation is learned from the coefficients themselves. The proposed reconstruction is suited for non-Cartesian, multi-channel data. The dictionary constraint leads to parameter maps with less noise and less aliasing for high amounts of acceleration.

Original language	English (US)
Title of host publication	Wavelets and Sparsity XVI
Editors	Vivek K. Goyal, Dimitri Van De Ville, Dimitri Van De Ville, Manos Papadakis, Dimitri Van De Ville, Manos Papadakis, Vivek K. Goyal, Dimitri Van De Ville
Publisher	SPIE
ISBN (Electronic)	9781628417630, 9781628417630
DOIs	https://doi.org/10.1117/12.2187088
State	Published - 2015
Event	Wavelets and Sparsity XVI - San Diego, United States Duration: Aug 10 2015 → Aug 12 2015

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	9597
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Wavelets and Sparsity XVI
Country/Territory	United States
City	San Diego
Period	8/10/15 → 8/12/15

Keywords

Compressed sensing
MRI
Radial
Sparsity
T

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.2187088

Cite this

Berman, B. P., Keerthivasan, M. B., Li, Z., Martin, D. R., Altbach, M. I., & Bilgin, A. (2015). Dictionary learning for compressive parameter mapping in magnetic resonance imaging. In V. K. Goyal, D. Van De Ville, D. Van De Ville, M. Papadakis, D. Van De Ville, M. Papadakis, V. K. Goyal, & D. Van De Ville (Eds.), Wavelets and Sparsity XVI Article 959707 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9597). SPIE. https://doi.org/10.1117/12.2187088

Dictionary learning for compressive parameter mapping in magnetic resonance imaging. / Berman, Benjamin P.; Keerthivasan, Mahesh B.; Li, Zhitao et al.
Wavelets and Sparsity XVI. ed. / Vivek K. Goyal; Dimitri Van De Ville; Dimitri Van De Ville; Manos Papadakis; Dimitri Van De Ville; Manos Papadakis; Vivek K. Goyal; Dimitri Van De Ville. SPIE, 2015. 959707 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9597).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Berman, BP, Keerthivasan, MB, Li, Z, Martin, DR, Altbach, MI & Bilgin, A 2015, Dictionary learning for compressive parameter mapping in magnetic resonance imaging. in VK Goyal, D Van De Ville, D Van De Ville, M Papadakis, D Van De Ville, M Papadakis, VK Goyal & D Van De Ville (eds), Wavelets and Sparsity XVI., 959707, Proceedings of SPIE - The International Society for Optical Engineering, vol. 9597, SPIE, Wavelets and Sparsity XVI, San Diego, United States, 8/10/15. https://doi.org/10.1117/12.2187088

Berman BP, Keerthivasan MB, Li Z, Martin DR, Altbach MI, Bilgin A. Dictionary learning for compressive parameter mapping in magnetic resonance imaging. In Goyal VK, Van De Ville D, Van De Ville D, Papadakis M, Van De Ville D, Papadakis M, Goyal VK, Van De Ville D, editors, Wavelets and Sparsity XVI. SPIE. 2015. 959707. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2187088

Berman, Benjamin P. ; Keerthivasan, Mahesh B. ; Li, Zhitao et al. / Dictionary learning for compressive parameter mapping in magnetic resonance imaging. Wavelets and Sparsity XVI. editor / Vivek K. Goyal ; Dimitri Van De Ville ; Dimitri Van De Ville ; Manos Papadakis ; Dimitri Van De Ville ; Manos Papadakis ; Vivek K. Goyal ; Dimitri Van De Ville. SPIE, 2015. (Proceedings of SPIE - The International Society for Optical Engineering).

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Dictionary learning for compressive parameter mapping in magnetic resonance imaging

Abstract

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Conference

Keywords

ASJC Scopus subject areas

Access to Document

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