Direction-adaptive grey-level morphology. application to 3D vascular brain imaging

Authors:
Olena Tankyevych;Hugues Talbot;Petr Dokládal;Nicolas Passat
Affiliations:
Université Paris-Est, Laboratoire d'Informatique Gaspard-Monge, Équipe A3SI, ESIEE Paris, Noisy-le-Grand Cedex, France;Université Paris-Est, Laboratoire d'Informatique Gaspard-Monge, Équipe A3SI, ESIEE Paris, Noisy-le-Grand Cedex, France;Centre de Morphologie Mathématique, Mines-Paristech, Fontainebeau, France;Université de Strasbourg, LSIIT, UMR, Strasbourg, France
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 7
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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 spatially-variant morphological filter for reconnection and reconstruction. The result is a fast and effective vessel-reconnecting method.