Daehyun Yoon1, Jeffrey Fessler1,
Jon-Fredrik Nielsen2, Anna Gilbert3, Douglas Noll2
1Electrical Engineering, University of
Michigan, Ann Arbor, MI, United States; 2Biomedical Engineering,
University of Michigan; 3Mathematics, University of Michigan
We
propose a novel, non-convex greedy compressed sensing algorithm for
phase-contrast MRI. Because the blood vessel distributions are sparse in the
image domain, we model that the velocity encoded image has only sparse phase
changes compared to the reference image without velocity encoding. Exploiting
this sparsity in the velocity encoding phase, we developed a non-convex
greedy compressed sensing algorithm to highly undersample the acquisition of
the velocity encoded object. We also compared our proposed method to a convex
optimization method and found out from the simulations that our method can
achieve higher undersampling rates.
Keywords