MODELING LONGITUDINAL MRI CHANGES IN POPULATIONS USING A LOCALIZED, INFORMATION-THEORETIC MEASURE OF CONTRAST.
Longitudinal MR imaging during early brain development provides important information about growth patterns and the development of neurological disorders. We propose a new framework for studying brain growth patterns within and across populations based on MRI contrast changes, measured at each time point of interest and at each voxel. Our method uses regression in the LogOdds space and an information-theoretic measure of distance between distributions to capture contrast in a manner that is robust to imaging parameters and without requiring intensity normalization. We apply our method to a clinical neuroimaging study on early brain development in autism, where we obtain a 4D spatiotemporal model of contrast changes in multimodal structural MRI.
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112.
Avantika
A
Vardhan
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112.
Marcel
M
Prastawa
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112.
Anuja
A
Sharma
Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599.
Joseph
J
Piven
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112.
Guido
G
Gerig
Contrast; Kullback-Leibler; longitudinal MRI; regression