Filtering and segmentation of 3D angiographic data: Advances based on mathematical morphology

Abstract : In the last 20 years, 3D angiographic imaging proved its usefulness in the context of various clinical applications. However, angiographic images are generally difficult to analyse due to their size and the fact that useful information is easily hidden in noise and artifacts. Therefore, there is an ongoing necessity to provide tools facilitating their visualization and analysis, while vessel segmentation from such images remains a challenging task. This article presents new vessel segmentation and filtering techniques, relying on recent advances in mathematical morphology. In particular, methodological results related to variant mathematical morphology and connected filtering are stated, and involved in an angiographic data processing framework. These filtering and segmentation methods are validated on real and synthetic 3D angiographic data.
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-00679008
Contributeur : Alice Dufour <>
Soumis le : mercredi 14 mars 2012 - 16:35:57
Dernière modification le : mercredi 28 septembre 2016 - 15:38:21
Document(s) archivé(s) le : vendredi 15 juin 2012 - 02:28:40

Fichier

HAL.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Alice Dufour, Olena Tankyevych, Benoît Naegel, Hugues Talbot, Christian Ronse, et al.. Filtering and segmentation of 3D angiographic data: Advances based on mathematical morphology. Medical Image Analysis, Elsevier, 2013, 17 (2), pp.147-164. <10.1016/j.media.2012.08.004>. <hal-00679008>

Partager

Métriques

Consultations de
la notice

419

Téléchargements du document

577