Quad-edge active contours for biomedical image segmentation

Daniel Felipe Gonzalez Obando (1) , Lauriane C Rohfritsch (1) , Manon C Faure (1) , Lydia C Danglot (2) , Vannary C Meas-Yedid (1) , Jean-Christophe C Olivo-Marin (1) , Alexandre C Dufour (1)

1 BIA - Analyse d'images biologiques - Biological Image Analysis
2 IJM (UMR_7592) - Institut Jacques Monod

We investigate a novel, parallel implementation of active contours for image segmentation combining a multi-agent system with a quad-edge representation of the contour. The control points of the contour evolve independently from one another in a parallel fashion, handling contour deformation, and convergence, while the quad-edge representation simplifies contour manipulation and local re-sampling during its evolution. We illustrate this new approach on biological images, and compare results with a conventional active contour implementation, discussing its benefits and limitations. This preliminary work is made freely available as a plug-in for our open-source Icy platform, where it will be developed with future extensions.

Mots clés: parallel computing; quad edge; active contours; Image segmentation; multi-agent systems

Domaines: Traitement du signal et de l'image [eess.SP]; Imagerie médicale; Imagerie

Daniel Felipe Gonzalez Obando, Lauriane C Rohfritsch, Manon C Faure, Lydia C Danglot, Vannary C Meas-Yedid, et al.. Quad-edge active contours for biomedical image segmentation. 2017 International Symposium on Biomedical Imaging (ISBI 2017), IEEE, Apr 2017, Melbourne, Australia. pp.1129-1132, ⟨10.1109/ISBI.2017.7950715⟩. ⟨hal-01578638⟩