Title
Infant brain probability templates for MRI segmentation and normalization.
Abstract
Spatial normalization and segmentation of infant brain MRI data based on adult or pediatric reference data may not be appropriate due to the developmental differences between the infant input data and the reference data. In this study we have constructed infant templates and a priori brain tissue probability maps based on the MR brain image data from 76 infants ranging in age from 9 to 15 months. We employed two processing strategies to construct the infant template and a priori data: one processed with and one without using a priori data in the segmentation step. Using the templates we constructed, comparisons between the adult templates and the new infant templates are presented. Tissue distribution differences are apparent between the infant and adult template, particularly in the gray matter (GM) maps. The infant a priori information classifies brain tissue as GM with higher probability than adult data, at the cost of white matter (WM), which presents with lower probability when compared to adult data. The differences are more pronounced in the frontal regions and in the cingulate gyrus. Similar differences are also observed when the infant data is compared to a pediatric (age 5 to 18) template. The two-pass segmentation approach taken here for infant T1W brain images has provided high quality tissue probability maps for GM, WM, and CSF, in infant brain images. These templates may be used as prior probability distributions for segmentation and normalization; a key to improving the accuracy of these procedures in special populations.
Year
DOI
Venue
2008
10.1016/j.neuroimage.2008.07.060
NeuroImage
Keywords
Field
DocType
artificial intelligence,magnetic resonance imaging,reference data,probability distribution,computer simulation,algorithms,brain imaging
Reference data (financial markets),Normalization (statistics),White matter,Computer science,Segmentation,A priori and a posteriori,Spatial normalization,Speech recognition,Gyrus,Prior probability
Journal
Volume
Issue
ISSN
43
4
1053-8119
Citations 
PageRank 
References 
30
1.57
7
Authors
4
Name
Order
Citations
PageRank
Mekibib Altaye1775.40
S. K. Holland26910.21
Marko Wilke321215.93
C Gaser440128.10