A unified non-rigid feature registration method for brain mapping

被引:55
|
作者
Chui, H
Win, L
Schultz, R
Duncan, JS
Rangarajan, A [1 ]
机构
[1] Univ Florida, Dept CISE, Gainesville, FL 32611 USA
[2] R2 Technol, Sunnyvale, CA USA
[3] Yale Univ, Yale Child Study Ctr, New Haven, CT USA
[4] Yale Univ, Dept Diagnost Radiol, New Haven, CT 06510 USA
关键词
non-rigid registration; brain mapping; sulci; MRI; clustering; deformation; feature-based; thin-plate splines; correspondence; mixture models; deterministic annealing;
D O I
10.1016/S1361-8415(02)00102-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes the design, implementation and results of a unified non-rigid feature registration method for the purposes of anatomical MRI brain registration. An important characteristic of the method is its ability to fuse different types of anatomical features into a single point-set representation. We demonstrate the application of the method using two different types of features: the outer cortical surface and major sulcal ribbons. Non-rigid registration of the combined feature point-sets is then performed using a new robust non-rigid point matching algorithm. The point matching algorithm implements an iterative joint clustering and matching (JCM) strategy which effectively reduces the computational complexity without sacrificing accuracy. We have conducted carefully designed synthetic experiments to gauge the effect of using different types of features either separately or together. A validation study examining the accuracy of non-rigid alignment of many brain structures is also presented. Finally, we present anecdotal results on the alignment of two subject MRI brain data. (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:113 / 130
页数:18
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