An unbiased iterative group registration template for cortical surface analysis

被引:341
作者
Lyttelton, Oliver
Boucher, Maxime
Robbins, Steven
Evans, Alan
机构
[1] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ H3A 2B4, Canada
[2] McGill Univ, Dept Biomed Engn, Montreal, PQ H3A 2B4, Canada
关键词
D O I
10.1016/j.neuroimage.2006.10.041
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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. (c) 2006 Elsevier Inc. All rights reserved.
引用
收藏
页码:1535 / 1544
页数:10
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