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Diffeomorphic Registration Using B-Splines

  • Daniel Rueckert
  • Paul Aljabar
  • Rolf A. Heckemann
  • Joseph V. Hajnal
  • Alexander Hammers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

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.

Keywords

Control Point Manual Segmentation Registration Algorithm Segmentation Propagation Diffeomorphic Transformation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Daniel Rueckert
    • 1
  • Paul Aljabar
    • 1
  • Rolf A. Heckemann
    • 2
  • Joseph V. Hajnal
    • 2
  • Alexander Hammers
    • 3
  1. 1.Department of ComputingImperial College LondonUK
  2. 2.Imaging Sciences Department, MRC Clinical Sciences CentreImperial College LondonUK
  3. 3.Division of Neuroscience and Mental Health, MRC Clinical Sciences CentreImperial College LondonUK

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