Real-time dynamic MR image reconstruction using Kalman Filtered Compressed Sensing

Authors:
Chenlu Qiu; Wei Lu;Namrata Vaswani
Affiliations:
Dept. of Electrical and Computer Engineering, Iowa State University, Ames, USA;Dept. of Electrical and Computer Engineering, Iowa State University, Ames, USA;Dept. of Electrical and Computer Engineering, Iowa State University, Ames, USA
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Abstract

In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measurements. In this work, we develop the KF-CS idea for causal reconstruction of medical image sequences from MR data. This is the first real application of KF-CS and is considerably more difficult than simulation data for a number of reasons, for example, the measurement matrix for MR is not as “incoherent” and the images are only compressible (not sparse). Greatly improved reconstruction results (as compared to CS and its recent modifications) on reconstructing cardiac and brain image sequences from dynamic MR data are shown.