Abstract #4274
Accelerated in vivo mapping of T 2 relaxation from radially undersampled datasets using compressed sensing and model-based reconstruction
Noam Ben-Eliezer 1 , Li Feng 1 , Kai Tobias Block 1 , Daniel K. Sodickson 1 , and Ricardo Otazo 1
1
Department of Radiology, New York University
School of Medicine, Bernard and Irene Schwartz Center
for Biomedical Imaging, New York, NY, United States
Accurate in vivo estimation of T
2
relaxation
values with high spatial resolution is very challenging
in clinical settings. This work, presents the fusion of
a recently-developed T
2
mapping
technique the echo-modulation curve (
EMC
)
algorithm with compressed sensing and model-based
reconstruction using undersampled radial trajectories.
The EMC approach avoids the common challenges associated
with stimulated echoes in multi spin-echo protocols,
while compressed sensing removes undersampling-related
aliasing artifacts. The synergistic combination of the
scanner-invariant EMC algorithm with a folding-free
radial sampling scheme offers accelerated quantification
of functional (T
2
) and morphological
(proton-density) information at sub-millimeter spatial
resolutions and with reduced sensitivity to motion.
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