Abstract #2586
Optimization of ROI transposition for atlas-based analysis of MRI quantitative metrics in neuroimaging studies
Mustafa Okan Irfanoglu 1,2 , Amritha Nayak 1,2 , Lindsay Walker 3 , Carlo Pierpaoli 1 , and The Brain Development Cooperative Group 4
1
NICHD, NIH, Bethesda, MD, United States,
2
CNRM,
USUHS, Bethesda, MD, United States,
3
Brown
University, RI, United States,
4
www.NIH-PediatricMRI.org,
MD, United States
In analyzing quantitative MRI metrics in large
population neuroimaging studies, it is convenient to
define ROIs on a representative atlas and then transpose
the ROIs onto individual subject space and extract
values. Here we assess the contribution to overall
variance that different ROI transformation methods
introduce on the analysis of developmental trajectories
of the diffusion MRI pediatric neuroimaging project, a
large database of more than 400 subjects age 0-20. We
find that the contribution to overall variance varies
significantly with various methods and we propose a
novel strategy that is more robust than previous
approaches.
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