Anatomical global spatial normalization

Abstract

Anatomical global spatial normalization (aGSN) is presented as a method to scale high-resolution brain images to control for variability in brain size without altering the mean size of other brain structures. Two types of mean preserving scaling methods were investigated, "shape preserving" and "shape standardizing". aGSN was tested by examining 56 brain structures from an adult brain atlas of 40 individuals (LPBA40) before and after normalization, with detailed analyses of cerebral hemispheres, all gyri collectively, cerebellum, brainstem, and left and right caudate, putamen, and hippocampus. Mean sizes of brain structures as measured by volume, distance, and area were preserved and variance reduced for both types of scale factors. An interesting finding was that scale factors derived from each of the ten brain structures were also mean preserving. However, variance was best reduced using whole brain hemispheres as the reference structure, and this reduction was related to its high average correlation with other brain structures. The fractional reduction in variance of structure volumes was directly related to ρ (2), the square of the reference-to-structure correlation coefficient. The average reduction in variance in volumes by aGSN with whole brain hemispheres as the reference structure was approximately 32%. An analytical method was provided to directly convert between conventional and aGSN scale factors to support adaptation of aGSN to popular spatial normalization software packages.

Fig. 1

Surface views of three brains from the LPBA40 database illustrating variation in size and shape. Surfaces extracted and views generated using Mango

Fig. 2

Examples of ROIs formulated from the LPBA40 database for one brain. Hemispheres and All Gyri in a & b are overlaid transparently onto the grey scale brain image

Fig. 3

Examples of three eigenvectors and three planar areas (dashed grey) used for analysis of scaling of linear distances and planar areas for right hippocampus

Fig. 4

Two scaling methods are illustrated for cerebellum: ICBM152 template using FLIRT (red) and aGSNs mean shape preserving (green). Natural cerebellum and brainstem are grey. Upper row is for a smaller than average size brain and lower row for a larger than average size brain. Note that aGSN scaling increased smaller and decreased larger cerebellum, while fitting using ICBM152 enlarged both

Fig. 5

The fraction of variance removed by mean preserving scaling is shown to be equivalent to that explained by regression analysis using brain structure as the regressor where the modeled R ² = ρ ²