Abstract #4265

Respiratory Motion Corrected 3D Patch based Reconstruction of Under-sampled Data for Liver 4D DCE-MRI

Dongxiao Li^1,2, Juerong Wu¹, Kofi M. Deh², Thanh D. Nguyen², Martin R. Prince², Yi Wang^2,3, and Pascal Spincemaille²

¹College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China, People's Republic of, ²Department of Radiology, Weill Cornell Medical College, New York, NY, United States, ³Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States

Liver dynamic contrast enhanced MRI (DCE-MRI) requires high spatial and temporal resolution such that all relevant enhancement phases are clearly visualized. Image quality is compromised when breathing occurs during the acquisition. This abstract presents a novel 4D respiratory Motion corrected Patch based Reconstruction of Under-sampled Data (M-PROUD) which uses 3D patch based local dictionaries for sparse coding and simultaneously estimates 3D nonrigid motion. Results on in vivo data demonstrated that the proposed method can significantly reduce motion blurring artifacts and preserve more details at a sub-second temporal frame rate in free breathing liver 4D DCE-MRI.

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