Diffeomorphic registration using b-splines

  • Authors:
  • Daniel Rueckert;Paul Aljabar;Rolf A. Heckemann;Joseph V. Hajnal;Alexander Hammers

  • Affiliations:
  • Department of Computing, Imperial College London, UK;Department of Computing, Imperial College London, UK;Imaging Sciences Department, MRC Clinical Sciences Centre, Imperial College London, UK;Imaging Sciences Department, MRC Clinical Sciences Centre, Imperial College London, UK;Division of Neuroscience and Mental Health, MRC Clinical Sciences Centre, Imperial College London, UK

  • Venue:
  • MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
  • Year:
  • 2006

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Abstract

In this paper we propose a diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines. In contrast to existing non-rigid registration methods based on FFDs the proposed diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines. To construct a diffeomorphic transformation we compose a sequence of free-form deformations while ensuring that individual FFDs are one-to-one transformations. We have evaluated the algorithm on 20 normal brain MR images which have been manually segmented into 67 anatomical structures. Using the agreement between manual segmentation and segmentation propagation as a measure of registration quality we have compared the algorithm to an existing FFD registration algorithm and a modified FFD registration algorithm which penalises non-diffeomorphic transformations. The results show that the proposed algorithm generates diffeomorphic transformations while providing similar levels of performance as the existing FFD registration algorithm in terms of registration accuracy.