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Abstract #4466

Model-based DTI reconstruction with sparsity constraints on the diffusion tensor

Florian Knoll 1 , Jos'e G Raya 1 , Rafael O Halloran 2 , Steven Beate 1 , Eric Sigmund 1 , Roland Bammer 2 , Tobias Block 1 , Ricardo Otazo 1 , and Daniel K Sodickson 1

1 Bernard & Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, New York, United States, 2 Radiology, Stanford University, Stanford, California, United States

DTI allows to obtain quantitative measurements of tissue microstructure that no other technique can reveal. A simple and well defined signal model exists for DTI, which makes it an ideal candidate for model-based methods. The goal of this study is to introduce a new combination of compressed sensing and model based reconstruction where the sparsifying transform is evaluated directly in the domain of the diffusion tensor. Experimental results for truly accelerated in-vivo imaging are shown for both brain an MSK applications which demonstrate excellent performance of the model based approach.

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