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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