title: An unbiased iterative group registration template for cortical surface analysis.
abstract: Accurate alignment of explicit surface representations of human cerebral cortices is necessary in order to compare local individual differences in cortical morphometric measurements (thickness, surface area, gyrification, etc.) in both normal and clinical populations. This paper presents a methodology for developing unbiased, high resolution iterative registration templates from a group of 222 subject hemispheres and shows that the resulting template provides better alignment of a separate set of test data than single-subject templates. It demonstrates that between 30 and 50 subjects are required to generate a stable iterative template. It also explores the way in which fold variants in registration templates affect the quality of registration. Finally, it shows that hemisphere-specific group registration templates systematically better register subject hemispheres of the same laterality, underlining the need to develop templates free of hemisphere bias for asymmetry analysis.
authors.affiliation: McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, Canada H3A 2B4.
authors.forename: Oliver
authors.initials: O
authors.lastname: Lyttelton
authors.forename: Maxime
authors.initials: M
authors.lastname: Boucher
authors.forename: Steven
authors.initials: S
authors.lastname: Robbins
authors.forename: Alan
authors.initials: A
authors.lastname: Evans
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D002540:Cerebral Cortex / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D012016:Reference Values; D012680:Sensitivity and Specificity