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Abstract #2617

Residual Reordering for Motion Compensated Compressed Sensing Cardiac Perfusion MR Imaging

Huisu Yoon1, Ganesh Adluru2, Edward V.R. DiBella2, Jong Chul Ye1

1Department of Bio and Brain Engineering, KAIST, Daejeon, Korea; 2Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, UT, United States

k-t FOCUSS with motion estimation and compensation is a promising tool for highly accelerated dynamic MRI. One of the limitations of k-t FOCUSS with ME/MC is, however, that the motion residual signals are often contaminated with background noises, so the reconstruction of the residual signal using standard l1 sparsity constraint are often inefficient in capturing the physiological features and results in temporal blurring. In this work, we exploit the reordering algorithm to make the residual reconstruction more efficient. Using cardiac perfusion imaging, the spatio-temporal constrained reconstruction using re-ordering was found effective for reconstruction of the motion residual in k-t FOCUSS with ME/MC. By combining k-t FOCUSS ME/MC, the ordering based residual reconstruction may be a useful tool for compressed sensing MRI.

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Keywords

accelerate acceleration according accurate acquisition adopt advanced aliasing alone applications applying artifacts assume axis background blurring blurry boundaries boundary brain capturing cardiac catch channel cine city clear clearly clinical coefficients coil combined compensated compensation compressed constrained constraint contaminated cost decomposed denotes derivative dose dynamic edge edges effective effectively efficient eight encoding engineering estimation every experimental exploit fast favored features forward foundation frame function generates gradient grant heartbeat important indicated inefficient initial iteratively lake limitations magnitude make mapping matrix model motion moving near noise noises often operator original part patient perfusion physiological pixel predefined predicted prediction profile profiles proposed radiology rather reconstruct reconstructed reconstructing reconstruction reconstructs recovery referred remain removing reordering represent represented represents residual residuals respectively resultant salt saturation scanner scheme science sensing short shot slice slices solution somewhat space sparsity specifically supported tagging taking temporal term theory third transform turbo univ unknown updated various wall walls