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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