2D Image-based reconstruction of shape deformation of biological structures using a level-set representation - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Computer Vision and Image Understanding Année : 2008

2D Image-based reconstruction of shape deformation of biological structures using a level-set representation

Résumé

This paper copes with the reconstruction of accretionary growth sequence from images of biological structures depicting concentric ring patterns. Accretionary growth shapes are modeled as the level-sets of a potential function. Given an image of a biological structure, the reconstruction of the sequence of growth shapes is stated as a variational issue derived from geometric criteria. This variational setting exploits image-based information, in terms of the orientation field of relevant image structures, which leads to an original advection term. The resolution of this variational issue is discussed. Experiments on synthetic and real data are reported to validate the proposed approach.
Fichier principal
Vignette du fichier
article_MottolithVision.pdf (821.79 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02344335 , version 1 (25-11-2019)

Identifiants

Citer

Ronan Fablet, Sylvain Pujolle, Anatole Chessel, Abdesslam Benzinou, Frédéric Cao. 2D Image-based reconstruction of shape deformation of biological structures using a level-set representation. Computer Vision and Image Understanding, 2008, 111 (3), pp.295 - 306. ⟨10.1016/j.cviu.2007.12.005⟩. ⟨hal-02344335⟩
32 Consultations
66 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More