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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