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ICASSP
2009
IEEE

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

10 years 4 months ago
Real-time dynamic MR image reconstruction using Kalman Filtered Compressed Sensing
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.
Chenlu Qiu, Wei Lu, Namrata Vaswani
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Chenlu Qiu, Wei Lu, Namrata Vaswani
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