Spherical Demons: Fast Surface Registration

B.T. Thomas Yeo (1) , Mert Sabuncu (1) , Tom Vercauteren (2) , Nicholas Ayache (3) , Bruce Fischl (1, 4) , Polina Golland (1)

1 CSAIL - Computer Science and Artificial Intelligence Laboratory [Cambridge]
2 Mauna Kea Technologies
3 ASCLEPIOS - Analysis and Simulation of Biomedical Images
4 Athinoula A. Martinos Center for Biomedical Imaging

We present the fast Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizers for the modified demons objective function can be efficiently implemented on the sphere using convolution. Based on the one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast -- registration of two cortical mesh models with more than 100k nodes takes less than 5 minutes, comparable to the fastest surface registration algorithms. Moreover, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different settings: (1) parcellation in a set of in-vivo cortical surfaces and (2) Brodmann area localization in ex-vivo cortical surfaces.

Domaines: Imagerie médicale

B.T. Thomas Yeo, Mert Sabuncu, Tom Vercauteren, Nicholas Ayache, Bruce Fischl, et al.. Spherical Demons: Fast Surface Registration. Medical Image Computing and Computer Assisted Intervention, Sep 2008, New York, United States. ⟨inria-00287048⟩