Average brain models: A convergence study

被引:299
作者
Guimond, A [1 ]
Meunier, J
Thirion, JP
机构
[1] Univ Montreal, Dept Informat & Rech Operat, Montreal, PQ H3C 3JC, Canada
[2] INRIA, Sophia Antipolis, Projet Epidaure, France
基金
加拿大自然科学与工程研究理事会;
关键词
D O I
10.1006/cviu.1999.0815
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a completely automatic method to build stable average anatomical models of the human brain using a set of magnetic resonance (MR) images. The models computed present two important characteristics: an average intensity and an average shape, both in a single image. We provide results showing convergence toward the centroid of the image set used for the computation of the model. In particular, the RMS distances between the model and the MR images contained in the set stabilize in a range of 2.88 to 3.36 mm from a range of 4.62 to 5.51 mm initially after only one iteration. As for the influence of the reference image chosen for the model construction, this is minimal with differences of about 1.0 mm, from approximately 3.5 mm initially. These results ensure the usefulness of our approach. (C) 2000 Academic Press.
引用
收藏
页码:192 / 210
页数:19
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