Open source ITK implementation of the symmetric demons

Post date: May 27, 2009 6:39:42 AM

Florence Dru and I have been working together to release the source code of the symmetric demons image registration algorithm that I presented at MICCAI 2008:

  • Tom Vercauteren, Xavier Pennec, Aymeric Perchant, and Nicholas Ayache. "Symmetric Log-Domain Diffeomorphic Registration: A Demons-based Approach." Proceedings of the 11th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2008), September 6 - 10 2008, New York, NY (pdf file)

This ITK source code has been released in the form of an Insight Journal submission:

  • Florence Dru and Tom Vercauteren. "An ITK Implementation of the Symmetric Log-Domain Diffeomorphic Demons Algorithm." Insight Journal , 2009 January - June (Available with source code here)
  • Abstract: This article provides an implementation of the symmetric log-domain diffeomorphic image registration algorithm, or symmetric demons algorithm for short. It generalizes Thirion's demons and the diffeomorphic demons algorithm. The main practical advantages of the symmetric demons with respect to the other demons variants is that is provides the inverse of the spatial transformation at no additional computational cost and ensures that the registration of image A to image B provides the inverse of the registration from image B to image A. The algorithm works completely in the log-domain, i.e. it uses a stationary velocity field to encode the spatial transformation as its exponential. Within the Insight Toolkit (ITK), the classical demons algorithm is implemented as part of the finite difference solver framework. Our code reuses and extends this generic framework. The source code is composed of a set of reusable ITK filters and classes together with their unit tests. We also provide a small example program that allows the user to compare the different variants of the demons algorithm. This paper gives an overview of the algorithm, an overview of its implementation and a small user guide to ease the use of the registration executable.

The Insight Journal is an Open Access on-line publication covering the domain of medical image processing and visualization. The unique characteristics of the Insight Journal include:

  • Open-access to articles, data, code, and reviews
  • Open peer-review that invites discussion between reviewers and authors
  • Emphasis on reproducible science via automated code compilation and testing
  • Support for continuous revision of articles, code, and revie

So if you find this code useful, please post a review on the Insight Journal: http://hdl.handle.net/10380/3060