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Abstract #2572

Super-resolution reconstruction of diffusion parameters from multi-oriented diffusion weighted images

Gwendolyn Van Steenkiste 1 , Ben Jeurissen 1 , Paul Parizel 2 , Dirk H.J. Poot 3,4 , and Jan Sijbers 1

1 iMinds Vision Lab, University of Antwerp, Wilrijk, Antwerp, Belgium, 2 department of Radiology, University of Antwerp, Antwerp, Belgium, 3 Imaging Science and Technology, Delft University of Technology, Delft, Netherlands, 4 BIGR (dept. of Medical informatics and Radiology), Erasmus Medical Center Rotterdam, Rotterdam, Netherlands

Diffusion weighted (DW) images are acquired with a low spatial resolution to obtain a reasonable signal-to-noise ratio within a clinically feasible scan time. Recently, a method has been proposed that improves this trade-off by acquiring multiple anisotropic DW images with different slice orientations, and recovering the underlying high resolution (HR) DW images via super-resolution reconstruction (SRR). Here, we present an improved method (SRR-DTI) which includes the diffusion tensor model. We show using whole brain tractography that fiber tracking in a SRR-DTI data set is more accurate than in a HR DW data set acquired within the same scan time.

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