Non-Euclidean image-adaptive Radial Basis Functions for 3D interactive segmentation

@article{Mory2009NonEuclideanIR,
  title={Non-Euclidean image-adaptive Radial Basis Functions for 3D interactive segmentation},
  author={Benoit Mory and Roberto Ardon and Anthony J. Yezzi and Jean-Philippe Thiran},
  journal={2009 IEEE 12th International Conference on Computer Vision},
  year={2009},
  pages={787-794}
}
In the context of variational image segmentation, we propose a new finite-dimensional implicit surface representation. The key idea is to span a subset of implicit functions with linear combinations of spatially-localized kernels that follow image features. This is achieved by replacing the Euclidean distance in conventional Radial Basis Functions with non-Euclidean, image-dependent distances. For the minimization of an objective region-based criterion, this representation yields more accurate… CONTINUE READING

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