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Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: block low-rank sparsity with motion-guidance (BLOSM).
Magn Reson Med 2014; 72(4):1028-38MR

Abstract

PURPOSE

Dynamic contrast-enhanced MRI of the heart is well-suited for acceleration with compressed sensing (CS) due to its spatiotemporal sparsity; however, respiratory motion can degrade sparsity and lead to image artifacts. We sought to develop a motion-compensated CS method for this application.

METHODS

A new method, Block LOw-rank Sparsity with Motion-guidance (BLOSM), was developed to accelerate first-pass cardiac MRI, even in the presence of respiratory motion. This method divides the images into regions, tracks the regions through time, and applies matrix low-rank sparsity to the tracked regions. BLOSM was evaluated using computer simulations and first-pass cardiac datasets from human subjects. Using rate-4 undersampling, BLOSM was compared with other CS methods such as k-t SLR that uses matrix low-rank sparsity applied to the whole image dataset, with and without motion tracking, and to k-t FOCUSS with motion estimation and compensation that uses spatial and temporal-frequency sparsity.

RESULTS

BLOSM was qualitatively shown to reduce respiratory artifact compared with other methods. Quantitatively, using root mean squared error and the structural similarity index, BLOSM was superior to other methods.

CONCLUSION

BLOSM, which exploits regional low-rank structure and uses region tracking for motion compensation, provides improved image quality for CS-accelerated first-pass cardiac MRI.

Authors+Show Affiliations

Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.No 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

24243528

Citation

Chen, Xiao, et al. "Motion-compensated Compressed Sensing for Dynamic Contrast-enhanced MRI Using Regional Spatiotemporal Sparsity and Region Tracking: Block Low-rank Sparsity With Motion-guidance (BLOSM)." Magnetic Resonance in Medicine, vol. 72, no. 4, 2014, pp. 1028-38.
Chen X, Salerno M, Yang Y, et al. Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: block low-rank sparsity with motion-guidance (BLOSM). Magn Reson Med. 2014;72(4):1028-38.
Chen, X., Salerno, M., Yang, Y., & Epstein, F. H. (2014). Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: block low-rank sparsity with motion-guidance (BLOSM). Magnetic Resonance in Medicine, 72(4), pp. 1028-38. doi:10.1002/mrm.25018.
Chen X, et al. Motion-compensated Compressed Sensing for Dynamic Contrast-enhanced MRI Using Regional Spatiotemporal Sparsity and Region Tracking: Block Low-rank Sparsity With Motion-guidance (BLOSM). Magn Reson Med. 2014;72(4):1028-38. PubMed PMID: 24243528.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: block low-rank sparsity with motion-guidance (BLOSM). AU - Chen,Xiao, AU - Salerno,Michael, AU - Yang,Yang, AU - Epstein,Frederick H, Y1 - 2013/11/18/ PY - 2013/07/01/received PY - 2013/09/11/revised PY - 2013/10/08/accepted PY - 2013/11/19/entrez PY - 2013/11/19/pubmed PY - 2015/5/23/medline KW - cardiac MRI KW - compressed sensing KW - dynamic contrast-enhanced MRI KW - motion compensation KW - regional sparsity KW - respiratory artifact SP - 1028 EP - 38 JF - Magnetic resonance in medicine JO - Magn Reson Med VL - 72 IS - 4 N2 - PURPOSE: Dynamic contrast-enhanced MRI of the heart is well-suited for acceleration with compressed sensing (CS) due to its spatiotemporal sparsity; however, respiratory motion can degrade sparsity and lead to image artifacts. We sought to develop a motion-compensated CS method for this application. METHODS: A new method, Block LOw-rank Sparsity with Motion-guidance (BLOSM), was developed to accelerate first-pass cardiac MRI, even in the presence of respiratory motion. This method divides the images into regions, tracks the regions through time, and applies matrix low-rank sparsity to the tracked regions. BLOSM was evaluated using computer simulations and first-pass cardiac datasets from human subjects. Using rate-4 undersampling, BLOSM was compared with other CS methods such as k-t SLR that uses matrix low-rank sparsity applied to the whole image dataset, with and without motion tracking, and to k-t FOCUSS with motion estimation and compensation that uses spatial and temporal-frequency sparsity. RESULTS: BLOSM was qualitatively shown to reduce respiratory artifact compared with other methods. Quantitatively, using root mean squared error and the structural similarity index, BLOSM was superior to other methods. CONCLUSION: BLOSM, which exploits regional low-rank structure and uses region tracking for motion compensation, provides improved image quality for CS-accelerated first-pass cardiac MRI. SN - 1522-2594 UR - https://www.unboundmedicine.com/medline/citation/24243528/Motion_compensated_compressed_sensing_for_dynamic_contrast_enhanced_MRI_using_regional_spatiotemporal_sparsity_and_region_tracking:_block_low_rank_sparsity_with_motion_guidance__BLOSM__ L2 - https://doi.org/10.1002/mrm.25018 DB - PRIME DP - Unbound Medicine ER -