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Abstract #3791

Novel Sparse Model and Reconstruction for Dynamic Contrast-Enhanced MRI

Qiu Wang 1 , Boris Mailhe 1 , Robert Grimm 2 , Marcel Dominik Nickel 2 , Kai Tobias Block 3 , Hersh Chandarana 3 , and Mariappan S. Nadar 1

1 Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, United States, 2 MR Application & Workflow Development, Siemens Healthcare, Erlangen, Germany, 3 Department of Radiology, New York University School of Medicine, New York, NY, United States

Dynamic contrast-enhanced MRI is widely used in clinical practice, due to its ability to reveal clinically significant pathology. Faster acquisition is critical since the acquisition has to be completed within a short time after contrast injection. Sparse-model based reconstruction is one of the techniques to recover high quality image for accelerated acquisitions. Sparse constraints correlated with the temporal dimension allow high spatio-temporal resolution. This work proposes a new sparse model and a reconstruction acceleration algorithm designed for DCE MRI. Experimental results demonstrate the effectiveness of the proposed method with superior image quality and time curves.

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