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Non-rigid Registration for Colorectal Cancer MR Images

  • Sarah L. Bond
  • J. Michael Brady
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3765)

Abstract

We are developing a system for patient management in colorectal cancer, in which the need for segmentation and non-rigid registration of pre- and post-therapy images arises. Several methods for non-rigid registration have been proposed, all of which embody a ’generic’ algorithm to solve registration, largely irrespective both of the kinds of images and of the application. We have evaluated several of these algorithms for this application and find their performance unsuitable for aligning pre- and post- therapy colorectal images. This leads us to identify some of the implicit assumptions and fundamental limitations of these algorithms. None of the currently available algorithms take into account the issue of scale salience and more importantly, none of the algorithms ”know” enough about colorectal MRI to focus their attention for registration on those parts of the image that are clinically important. Based on this analysis, we propose a way in which we can perform registration by mobilizing the knowledge of the particular application, for example the prior shape knowledge that we have within the colorectal images as well as knowledge of the large scale non-rigid changes due to therapy.

Keywords

Mutual Information Breast Magnetic Resonance Image Registration Algorithm Weighted Magnetic Resonance Patient Management Decision 
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 2005

Authors and Affiliations

  • Sarah L. Bond
    • 1
  • J. Michael Brady
    • 1
  1. 1.Wolfson Medical Vision Laboratory, Department of Engineering ScienceUniversity of OxfordOxfordUK

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