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Spherical Demons: Fast Surface Registration

B. T. Thomas Yeo1, Mert Sabuncu1, Tom Vercauteren2, Nicholas Ayache3, Bruce Fischl4, 1 and Polina Golland1

(1)  Computer Science and Artificial Intelligence Laboratory, MIT,  , USA
(2)  Mauna Kea Technologies, Paris, France
(3)  Asclepios Group, INRIA, France
(4)  Athinoula A. Martinos Center for Biomedical Imaging, MGH/HMS, USA
Abstract
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.

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