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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.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Altaye M,Holland SK,Wilke M,Gaser C

doi

10.1016/j.neuroimage.2008.07.060

subject

Has Abstract

pub_date

2008-12-01 00:00:00

pages

721-30

issue

4

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(08)00896-3

journal_volume

43

pub_type

杂志文章

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