A Combined Segmentation and Registration Framework with a Nonlinear Elasticity Smoother

Authors:
Carole Guyader;Luminita A. Vese
Affiliations:
IRMAR, UMR CNRS 6625 Institut National des Sciences Appliquées de Rennes, RENNES Cedex, France 35043;Department of Mathematics, University of California, Los Angeles, Los Angeles, USA CA 90095-1555
Venue:
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Year:
2009

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Abstract

In this paper, we present a new non-parametric combined segmentation and registration method. The problem is cast as an optimization one, combining a matching criterion based on the active contour without edges [4] for segmentation, and a nonlinear-elasticity-based smoother on the displacement vector field. This modeling is twofold: first, registration is jointly performed with segmentation since guided by the segmentation process; it means that the algorithm produces both a smooth mapping between the two shapes and the segmentation of the object contained in the reference image. Secondly, the use of a nonlinear-elasticity-type regularizer allows large deformations to occur, which makes the model comparable in this point with the viscous fluid registration method [7]. Several applications are proposed to demonstrate the potential of this method to both segmentation of one single image and to registration between two images.