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Free Form Deformations Guided by Gradient Vector Flow: A Surface Registration Method in Thoracic and Abdominal PET-CT Applications

  • Oscar Camara
  • Gaspar Delso
  • Isabelle Bloch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2717)

Abstract

A nonlinear surface registration algorithm of thoracic/abdominal structures segmented from CT and PET volumes is presented. The aim of this work is to develop a method that can provide an initial estimate of the elastic deformation between the images, so that MI-based techniques can be successfully applied. To perform the matching, a B-spline Free Form Deformation (FFD) model has been chosen. Hierarchical structure segmentation and rigid registration are applied to initialize the nonlinear surface registration phase. Two different approaches to optimize the warp are tested: an iterative gradient descent technique based on local gradient estimations over the grid of control points; and an original optimization based on Gradient Vector Flow (GVF) computed on the CT image. Finally, we evaluate our results, using an Iterative Closest Point (ICP) rigid registration algorithm as a reference to compare both approaches.

Keywords

Positron Emission Tomography Root Mean Square Positron Emission Tomography Image Iterative Close Point Iterative Close Point 
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 2003

Authors and Affiliations

  • Oscar Camara
    • 1
  • Gaspar Delso
    • 1
  • Isabelle Bloch
    • 1
  1. 1.Département TSIEcole Nationale Supérieure des TélécommunicationsParisFrance

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