Seminar Details
2016-03-15 (14:00) : Cell Segmentation with Random Ferns and Graph Cuts
At Euler building (A002)
Organized by Mathematical Engineering
Speaker :
Browet, Arnaud
Abstract :
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 a random ferns classifier. 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 and demonstrate that our segmentation procedure is in very good agreement with the ground-truth defined by biologists.