A unified non-rigid feature registration method for brain mapping.
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.
Chui
Haili
H
R2 Technologies, Sunnyvale, CA, USA.
Win
Lawrence
L
Schultz
Robert
R
Duncan
James S
JS
Rangarajan
Anand
A
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008297:Male; D019047:Phantoms, Imaging