Optimizing Q-Space Sampling Density for Diffusion Spectrum Imaging
Qiyuan Tian 1 , Ariel Rokem 2 , Brian L. Edlow 3 , Rebecca D. Folkerth 4 , and Jennifer A. McNab 5
Department of Electrical Engineering,
Stanford University, Stanford, CA, United States,
of Psychology, Stanford University, Stanford, CA, United
of Neurology, Massachusetts General Hospital, Boston,
MA, United States,
of Pathology, Brigham and Women's Hospital, Boston, MA,
of Radiology, Stanford University, Stanford, CA, United
Diffusion spectrum imaging is an approach to
characterizing complex tissue microstructure. Stronger
gradients enable expanded q-space coverage, which
improves the spin-displacement resolution but also
increases the q-space sampling density requirements.
Here, we show three datasets acquired on a whole, fixed,
human brain acquired with 300mT/m maximum gradients.
These data are used to examine the effects of q-space
sampling density on the fidelity of the voxel-wise
orientation distribution functions (ODFs). Specifically,
we show there is trade-off between ODF sharpness and
aliasing artifacts when sampling density is insufficient
to capture the spin-displacement pattern.
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