Direction-Adaptive Grey-level Morphology. Application to 3D Vascular Brain Imaging

Abstract : Segmentation and analysis of blood vessels is an important issue in medical imaging. In 3D cerebral angiographic data, the vascular signal is however hard to accurately detect and can, in particular, be disconnected. In this article, we present a procedure utilising both linear, Hessian-based and morphological methods for blood vessel edge enhancement and reconnection. More specifically, multi-scale second-order derivative analysis is performed to detect candidate vessels as well as their orientation. This information is then fed to a spatiallyvariant morphological filter for reconnection and reconstruction. The result is a fast and effective vessel-reconnecting method.
Type de document :
Communication dans un congrès
16th IEEE International Conference on Image Processing (ICIP), Nov 2009, Le Caire, Egypt. IEEE, pp.2261-2264, 2009, 〈10.1109/ICIP.2009.5414356〉
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https://hal-upec-upem.archives-ouvertes.fr/hal-00622439
Contributeur : Talbot Hugues <>
Soumis le : lundi 12 septembre 2011 - 14:16:41
Dernière modification le : vendredi 27 octobre 2017 - 17:36:02

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Olena Tankyevych, Hugues Talbot, Petr Dokládal, Nicolas Passat. Direction-Adaptive Grey-level Morphology. Application to 3D Vascular Brain Imaging. 16th IEEE International Conference on Image Processing (ICIP), Nov 2009, Le Caire, Egypt. IEEE, pp.2261-2264, 2009, 〈10.1109/ICIP.2009.5414356〉. 〈hal-00622439〉

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