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Compressed sensing reconstruction for whole-heart imaging with 3D radial trajectories: a graphics processing unit implementation.
Magn Reson Med. 2013 Jan; 69(1):91-102.MR

Abstract

A disadvantage of three-dimensional (3D) isotropic acquisition in whole-heart coronary MRI is the prolonged data acquisition time. Isotropic 3D radial trajectories allow undersampling of k-space data in all three spatial dimensions, enabling accelerated acquisition of the volumetric data. Compressed sensing (CS) reconstruction can provide further acceleration in the acquisition by removing the incoherent artifacts due to undersampling and improving the image quality. However, the heavy computational overhead of the CS reconstruction has been a limiting factor for its application. In this article, a parallelized implementation of an iterative CS reconstruction method for 3D radial acquisitions using a commercial graphics processing unit is presented. The execution time of the graphics processing unit-implemented CS reconstruction was compared with that of the C++ implementation, and the efficacy of the undersampled 3D radial acquisition with CS reconstruction was investigated in both phantom and whole-heart coronary data sets. Subsequently, the efficacy of CS in suppressing streaking artifacts in 3D whole-heart coronary MRI with 3D radial imaging and its convergence properties were studied. The CS reconstruction provides improved image quality (in terms of vessel sharpness and suppression of noise-like artifacts) compared with the conventional 3D gridding algorithm, and the graphics processing unit implementation greatly reduces the execution time of CS reconstruction yielding 34-54 times speed-up compared with C++ implementation.

Authors+Show Affiliations

Cardiovascular Division, Department of Medicine, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215, USA.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

22392604

Citation

Nam, Seunghoon, et al. "Compressed Sensing Reconstruction for Whole-heart Imaging With 3D Radial Trajectories: a Graphics Processing Unit Implementation." Magnetic Resonance in Medicine, vol. 69, no. 1, 2013, pp. 91-102.
Nam S, Akçakaya M, Basha T, et al. Compressed sensing reconstruction for whole-heart imaging with 3D radial trajectories: a graphics processing unit implementation. Magn Reson Med. 2013;69(1):91-102.
Nam, S., Akçakaya, M., Basha, T., Stehning, C., Manning, W. J., Tarokh, V., & Nezafat, R. (2013). Compressed sensing reconstruction for whole-heart imaging with 3D radial trajectories: a graphics processing unit implementation. Magnetic Resonance in Medicine, 69(1), 91-102. https://doi.org/10.1002/mrm.24234
Nam S, et al. Compressed Sensing Reconstruction for Whole-heart Imaging With 3D Radial Trajectories: a Graphics Processing Unit Implementation. Magn Reson Med. 2013;69(1):91-102. PubMed PMID: 22392604.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Compressed sensing reconstruction for whole-heart imaging with 3D radial trajectories: a graphics processing unit implementation. AU - Nam,Seunghoon, AU - Akçakaya,Mehmet, AU - Basha,Tamer, AU - Stehning,Christian, AU - Manning,Warren J, AU - Tarokh,Vahid, AU - Nezafat,Reza, Y1 - 2012/03/05/ PY - 2011/06/24/received PY - 2012/01/16/revised PY - 2012/02/06/accepted PY - 2012/3/7/entrez PY - 2012/3/7/pubmed PY - 2013/6/8/medline SP - 91 EP - 102 JF - Magnetic resonance in medicine JO - Magn Reson Med VL - 69 IS - 1 N2 - A disadvantage of three-dimensional (3D) isotropic acquisition in whole-heart coronary MRI is the prolonged data acquisition time. Isotropic 3D radial trajectories allow undersampling of k-space data in all three spatial dimensions, enabling accelerated acquisition of the volumetric data. Compressed sensing (CS) reconstruction can provide further acceleration in the acquisition by removing the incoherent artifacts due to undersampling and improving the image quality. However, the heavy computational overhead of the CS reconstruction has been a limiting factor for its application. In this article, a parallelized implementation of an iterative CS reconstruction method for 3D radial acquisitions using a commercial graphics processing unit is presented. The execution time of the graphics processing unit-implemented CS reconstruction was compared with that of the C++ implementation, and the efficacy of the undersampled 3D radial acquisition with CS reconstruction was investigated in both phantom and whole-heart coronary data sets. Subsequently, the efficacy of CS in suppressing streaking artifacts in 3D whole-heart coronary MRI with 3D radial imaging and its convergence properties were studied. The CS reconstruction provides improved image quality (in terms of vessel sharpness and suppression of noise-like artifacts) compared with the conventional 3D gridding algorithm, and the graphics processing unit implementation greatly reduces the execution time of CS reconstruction yielding 34-54 times speed-up compared with C++ implementation. SN - 1522-2594 UR - https://www.unboundmedicine.com/medline/citation/22392604/Compressed_sensing_reconstruction_for_whole_heart_imaging_with_3D_radial_trajectories:_a_graphics_processing_unit_implementation_ L2 - https://doi.org/10.1002/mrm.24234 DB - PRIME DP - Unbound Medicine ER -