An efficient ADMM-based sparse reconstruction strategy for multi-level sampled MRI

Joshua D Trazasko, Eric A. Borisch, Paul T. Weavers, Armando Manduca, Phillip M. Young, Stephen J Riederer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Sparsity-driven image reconstruction is a promising paradigm for improving the spatial, temporal, and contrast resolution in magnetic resonance imaging (MRI). However, high computational expense continues to inhibit the translation of these techniques into routine clinical practice. In many MRI acquisition protocols (e.g., time-resolved CAPR), the sampling operator can be factored into a uniform and non-uniform component. In this work, we present a novel alternating direction method-of-multipliers (ADMM) strategy for sparse reconstruction of multilevel sampled Cartesian SENSE-type MRI data, and discuss how this framework enables certain operations to be computed once offline and recycled during the reconstruction process rather than repeated at every iteration. We then demonstrate that this algorithmic framework enables sparse reconstruction of 3D contrast-enhanced MR angiogram (CE-MRA) time-series in just several minutes (which is clinically practical) rather than the several hours previously required.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages411-414
Number of pages4
Volume2015-April
ISBN (Print)9781479982974
DOIs
StatePublished - Apr 24 2015
Event48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 2 2014Nov 5 2014

Other

Other48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/2/1411/5/14

Fingerprint

Magnetic resonance
Imaging techniques
Image reconstruction
Mathematical operators
Time series
Sampling

Keywords

  • ADMM
  • Low-Rank
  • MRI
  • Sparse

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

Cite this

Trazasko, J. D., Borisch, E. A., Weavers, P. T., Manduca, A., Young, P. M., & Riederer, S. J. (2015). An efficient ADMM-based sparse reconstruction strategy for multi-level sampled MRI. In Conference Record - Asilomar Conference on Signals, Systems and Computers (Vol. 2015-April, pp. 411-414). [7094474] IEEE Computer Society. https://doi.org/10.1109/ACSSC.2014.7094474

An efficient ADMM-based sparse reconstruction strategy for multi-level sampled MRI. / Trazasko, Joshua D; Borisch, Eric A.; Weavers, Paul T.; Manduca, Armando; Young, Phillip M.; Riederer, Stephen J.

Conference Record - Asilomar Conference on Signals, Systems and Computers. Vol. 2015-April IEEE Computer Society, 2015. p. 411-414 7094474.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Trazasko, JD, Borisch, EA, Weavers, PT, Manduca, A, Young, PM & Riederer, SJ 2015, An efficient ADMM-based sparse reconstruction strategy for multi-level sampled MRI. in Conference Record - Asilomar Conference on Signals, Systems and Computers. vol. 2015-April, 7094474, IEEE Computer Society, pp. 411-414, 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015, Pacific Grove, United States, 11/2/14. https://doi.org/10.1109/ACSSC.2014.7094474
Trazasko JD, Borisch EA, Weavers PT, Manduca A, Young PM, Riederer SJ. An efficient ADMM-based sparse reconstruction strategy for multi-level sampled MRI. In Conference Record - Asilomar Conference on Signals, Systems and Computers. Vol. 2015-April. IEEE Computer Society. 2015. p. 411-414. 7094474 https://doi.org/10.1109/ACSSC.2014.7094474
Trazasko, Joshua D ; Borisch, Eric A. ; Weavers, Paul T. ; Manduca, Armando ; Young, Phillip M. ; Riederer, Stephen J. / An efficient ADMM-based sparse reconstruction strategy for multi-level sampled MRI. Conference Record - Asilomar Conference on Signals, Systems and Computers. Vol. 2015-April IEEE Computer Society, 2015. pp. 411-414
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