Paper Info
Title
Modeling longitudinal MRI changes in populations using a localized, information-theoretic measure of contrast
Abstract
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.
Year
DOI
Venue
2013
10.1109/ISBI.2013.6556794
Biomedical Imaging
Keywords
Field
DocType
biomedical MRI,brain,medical disorders,medical image processing,neurophysiology,physiological models,regression analysis,spatiotemporal phenomena,4D spatiotemporal model,LogOdds space,autism,brain development,brain growth pattern,information-theoretic constrat measure,longitudinal MRI contrast change modeling,magnetic resonance imaging,multimodal structural MRI,neuroimaging study,neurological disorder development,regression method,voxel,Contrast,Kullback-Leibler,longitudinal MRI,regression
Voxel,Time point,Normalization (statistics),Neurophysiology,Pattern recognition,Regression,Computer science,Artificial intelligence,Neuroimaging,Statistical distance,Kullback–Leibler divergence
Conference
Volume
ISSN
ISBN
2013
1945-7928
978-1-4673-6456-0
Citations 
PageRank 
References 
0
0.34
5
Authors
4
Name
Order
Citations
PageRank
Vardhan, A.100.34
Prastawa, M.271.31
A. K. Sharma361.48
Piven Joseph477049.65