Simultaneous Image Segmentation and Medial Structure Estimation - Application to 2D and 3D Vessel Tree Extraction - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2011

Simultaneous Image Segmentation and Medial Structure Estimation - Application to 2D and 3D Vessel Tree Extraction

Résumé

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
Fichier principal
Vignette du fichier
MakramEbeid_SPIE2011.pdf (3.15 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-00594714 , version 1 (20-05-2011)

Identifiants

Citer

Sherif Makram-Ebeid, Jean Stawiaski, Guillaume Pizaine. Simultaneous Image Segmentation and Medial Structure Estimation - Application to 2D and 3D Vessel Tree Extraction. SPIE Medical Imaging 2011: Image Processing, Feb 2011, Orlando, FL, United States. pp.79623D, ⟨10.1117/12.878126⟩. ⟨hal-00594714⟩
98 Consultations
114 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More