Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Biased anisotropic diffusion: a unified regularization and diffusion approach to edge detection
Image and Vision Computing - Special issue on the first ECCV 1990
Image selective smoothing and edge detection by nonlinear diffusion. II
SIAM Journal on Numerical Analysis
International Journal of Computer Vision
Journal of Mathematical Imaging and Vision - Special issue on mathematical imaging
Deformable Models For Reconstructing Unstructured 3D Data
CVRMed '95 Proceedings of the First International Conference on Computer Vision, Virtual Reality and Robotics in Medicine
CVRMed '95 Proceedings of the First International Conference on Computer Vision, Virtual Reality and Robotics in Medicine
Brain Morphometry by Distance Measurement in a Non-Euclidean, Curvilinear Space
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Anatomically constrained surface parameterization for cortical localization
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
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This paper proposes an alternative to mathematical morphology to analyze complex shapes. This approach aims mainly at the detection of shape bottlenecks which are often of interest in medical imaging because of their anatomical meaning. The detection idea consists in simulating the steady state of an information transmission process between two parts of a complex object in order to highlight bottlenecks as areas of high information flow. This information transmission process is supposed to have a conservative flow which leads to the well-known Dirichlet-Neumann problem. This problem is solved using finite differences, over-relaxation and a raw to fine implementation. The method is applied to the detection of main bottlenecks of brain white matter network, namely corpus callosum, anterior commissure and brain stem.