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* Corresponding author 1 Medisys - MedisysResearch Lab 2 LTCI - Laboratoire Traitement et Communication de l-Information

Abstract : We propose a variational approach which combines automatic segmentation and medial structure extraction in a single computationally efficient algorithm. In this paper, we apply our approach to the analysis of vessels in 2D X-ray angiography and 3D X-ray rotational angiography of the brain. Other variational methods proposed in the literature encode the medial structure of vessel trees as a skeleton with associated vessel radii. In contrast, our method provides a dense smooth level set map which sign provides the segmentation. The ridges of this map define the segmented regions skeleton. The differential structure of the smooth map in particular the Hessian allows the discrimination between tubular and other structures. In 3D, both circular and non-circular tubular cross-sections and tubular branching can be handled conveniently. This algorithm allows accurate segmentation of complex vessel structures. It also provides key tools for extracting anatomically labeled vessel tree graphs and for dealing with challenging issues like kissing vessel discrimination and separation of entangled 3D vessel trees. ©2011 COPYRIGHT SPIE-The International Society for Optical Engineering. Please use http:-dx.doi.org-10.1117-12.878126

Mots-clés : Variational Techniques Finite Elements Medial Structure Vessel Tree Segmentation





Autor: Sherif Makram-Ebeid - Jean Stawiaski - Guillaume Pizaine -

Fuente: https://hal.archives-ouvertes.fr/



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