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Nonrigid Registration Using Regularized Matching Weighted by Local Structure

  • Eduardo Suárez
  • Carl-Fredrik Westin
  • Eduardo Rovaris
  • Juan Ruiz-Alzola
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2489)

Abstract

We present a novel approach to nonrigid registration of volumetric multimodal medical data. We propose a new regularized template matching scheme, where arbitrary similarity measures can be embedded and the regularization imposes spatial coherence taking into account the quality of the matching according to an estimation of the local structure. We propose to use an efficient variation of weighted least squares termed normalized convolution as a mathematically coherent framework for the whole approach. Results show that our method is fast as accurate.

Keywords

Root Mean Square Local Structure Template Match Spatial Coherence Nonrigid Registration 
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 2002

Authors and Affiliations

  • Eduardo Suárez
    • 1
  • Carl-Fredrik Westin
    • 2
  • Eduardo Rovaris
    • 1
  • Juan Ruiz-Alzola
    • 1
    • 2
  1. 1.Medical Technology CenterUniv. Las Palmas of GC & Gran Canaria Dr. Negrín HospitalSpain
  2. 2.Laboratory of Mathematics in ImagingBrigham and Women’s Hospital and Harvard Medical SchoolUSA

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