Title :
Geodesic Active Fields on the Sphere
Author :
Zosso, Dominique ; Thiran, Jean-Philippe
Author_Institution :
Signal Process. Lab. LTS5, Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland
Abstract :
In this paper, we propose a novel method to register images defined on spherical meshes. Instances of such spherical images include inflated cortical feature maps in brain medical imaging or images from omni directional cameras. We apply the Geodesic Active Fields (GAF) framework locally at each vertex of the mesh. Therefore we define a dense deformation field, which is embedded in a higher dimensional manifold, and minimize the weighted Polyakov energy. While the Polyakov energy itself measures the hyper area of the embedded deformation field, its weighting allows to account for the quality of the current image alignment. Iteratively minimizing the energy drives the deformation field towards a smooth solution of the registration problem. Although the proposed approach does not necessarily outperform state-of-the-art methods that are tightly tailored to specific applications, it is of methodological interest due to its high degree of flexibility and versatility.
Keywords :
brain; computational geometry; feature extraction; image registration; medical image processing; mesh generation; brain medical imaging; deformation field; geodesic active field; image alignment; image registration; inflated cortical feature map; mesh vertex; omnidirectional camera; spherical image; spherical mesh; weighted Polyakov energy; Deformable models; Equations; Image registration; Manifolds; Minimization; Noise reduction; Surface treatment; Biomedical image processing; Computational geometry; Differential geometry; Diffusion equations; Image registration; Scale-spaces; Spheres; Surfaces;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.1089