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Abstract #2162

Patch-Based Reconstruction Of Undersampled Images (PROUD) for Sub-second Frame Rate 4D Contrast Enhanced Liver Imaging

Mitchell Anthony Cooper 1,2 , Pascal Spincemaille 2 , Bo Xu 1,2 , Thanh D Nguyen 2 , Martin R. Prince 2 , Michael Elad 3 , and Yi Wang 1,2

1 Biomedical Engineering, Cornell University, Ithaca, New York, United States, 2 Radiology, Weill Cornell Medical College, New York, New York, United States, 3 Computer Science, Technion - Israel Institute of Technology, Haifa, Israel

High temporal & spatial resolution 4D imaging with large volume coverage is needed to accurately capture organ perfusion. Typically, parallel-imaging reconstruction is done to achieve high frame rate and large volume coverage and results in a loss of signal to noise ratio compared to Nyquist sampling. Furthermore, residual under-sampling artifacts are temporally varying and complicate the quantitative analysis of contrast enhancement curves needed for pharmacokinetic modeling. Here, we propose a method, Patch based Reconstruction Of Undersampled Data or PROUD, that will both improve noise characteristics as well as minimize temporally-varying residual artifacts.

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