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Performance Comparison of Compressed Sensing Algorithms for Accelerating T1ρ Mapping of Human Brain

Rajiv G Menon1, Marcelo V W Zibetti1, Rajan Jain2,3

  • 1Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, New York, USA.

Journal of Magnetic Resonance Imaging : JMRI
|November 15, 2020
PubMed
Summary

Compressed sensing algorithms significantly reduce scan times for 3D-T1ρ brain mapping. Spatiotemporal finite differences (STFD) and exponential dictionary (EXP) methods offer efficient quantitative imaging for neurologic disorders.

Keywords:
T1ρ mappingbrain imagingcompressed sensinglow rank modelssparse reconstruction

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Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).