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 Bspline Free Form Deformation (FFD) model has been chosen. Hierarchical structure segmentation and rigid registration are applied to initialize the nonlinear

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... e 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.