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Abstract #2262

A Block Reordering Technique in a Compressed Sensing Framework

Srikant Kamesh Iyer1, 2, Tolga Tasdizen3, 4, Ganesh Adluru5, Edward DiBella6, 7

1Electrical and Computer Engineering , University of Utah , salt lake city, UT, United States; 2Scientific Computing and Imaging Institute (SCI), University Of Utah, salt lake city, UT, United States; 3Electrical and Computer Engineering, University of Utah, salt lake city, UT, United States; 4Scientific Computing and Imaging Institute (SCI), University Of Utah , salt lake city, UT, United States; 5UCAIR, Department of Radiology, University of Utah, salt lake city, UT, United States; 6UCAIR, Department of Radiology,, University of Utah, salt lake city, UT, United States; 7Department of Bioengineering, , University of Utah, salt lake city, UT, United States

Incorporating priors about the order of signal intensities of pixels to modify the TV constraint has been shown to improve the quality of the images reconstructed from under sampled data. We propose to apply the pixel ordering information by dividing the data into smaller blocks to make the method more robust to motion. Comparisons with TCR and TCR with single block reordering show that that smaller block size help improve the robustness of the reconstruction to motion in the data and the reconstructions match the fully sampled data more faithfully.

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Keywords

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