Spherical demons: fast surface registration. Academic Article uri icon

Overview

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.

publication date

  • January 1, 2008

Research

keywords

  • Artificial Intelligence
  • Brain
  • Image Interpretation, Computer-Assisted
  • Imaging, Three-Dimensional
  • Magnetic Resonance Imaging
  • Pattern Recognition, Automated
  • Subtraction Technique

Identity

PubMed Central ID

  • PMC2792585

Scopus Document Identifier

  • 84883845923

Digital Object Identifier (DOI)

  • 10.1007/978-3-540-85988-8_89

PubMed ID

  • 18979813

Additional Document Info

volume

  • 11

issue

  • Pt 1