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Abstract #2622

Accelerated Myocardial Perfusion MRI Using Motion Compensated Compressed Sensing (MC-CS)

Sajan Goud Lingala1, Edward V.R. DiBella2, Mathews Jacob1

1The University of Iowa, Iowa city, IA, United States; 2University of Utah, Salt lake city, UT, United States

We propose a novel motion compensated compressed sensing reconstruction scheme for myocardial perfusion MRI. We develop an efficient energy minimization framework that jointly estimates the motion and the dynamic images from undersampled data. Our preliminary results show that proposed scheme is able to considerably reduce motion related artifacts in temporally constrained compressed sensing reconstruction.

Keywords

able accelerated accurately added amplify arrows artifacts auxiliary better blur blurring bottom breathing challenge city coil coils compensate compensated compensation compressed considerable considered constrained constraint contained contrast correct corrected corrects coverage criterion customized dataset decreases deformable deformation detail determine domain domains dynamic enforce especially essentially estimation evident exam examples experiment extensions fidelity finally find fixing flash form frame frames free fully gating gradient grid improve inconsistent initialize introducing iterative jointly lake loss maps minimization model motion myocardial navigators necessary noise novel operator optimization overcome patient penalty performance perfusion posed preliminary problem profile proposed quadratic quantify radial rays read reconstructing reconstruction reconstructions recovery reduce registering registration regularization related require resolution retrospectively rigid robust rotations salt sampled saturation scheme sensing sensitivity series shrinkage significantly simple simplification simplify simulation slice slices smoothing solve spaced sparsity spatial specifically specified start step steps strategy stress suboptimal suffer temporal third trajectory uniform update variation varies warped warping