par Browet, Arnaud;De Vleeschouwer, Christophe;Jacques, Laurent;Mathiah, Navrita 
;Saykali, Bechara ;Migeotte, Isabelle
Référence Proceedings - International Conference on Image Processing, 2016-August, page (4145-4149), 7533140
Publication Publié, 2016-08
;Saykali, Bechara ;Migeotte, Isabelle Référence Proceedings - International Conference on Image Processing, 2016-August, page (4145-4149), 7533140
Publication Publié, 2016-08
Article révisé par les pairs
| Résumé : | The progress in imaging techniques have allowed the study of various aspect of cellular mechanisms. To isolate individual cells in live imaging data, we introduce an elegant image segmentation framework that effectively extracts cell boundaries, even in the presence of poor edge details. Our approach works in two stages. First, we estimate pixel interior/border/exterior class probabilities using random ferns. Then, we use an energy minimization framework to compute boundaries whose localization is compliant with the pixel class probabilities. We validate our approach on a manually annotated dataset. |
