Cell segmentation with random ferns and graph-cuts

A. Browet, C. De Vleeschouwer, L. Jacques, N. Mathiah, B. Saykali, I. Migeotte
2016 2016 IEEE International Conference on Image Processing (ICIP)  
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
more » ... is compliant with the pixel class probabilities. We validate our approach on a manually annotated dataset.
doi:10.1109/icip.2016.7533140 dblp:conf/icip/BrowetVJMSM16 fatcat:3qghy4emgnacliy4v6am46rehe