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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