Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The progress in imaging techniques have allod the study of#N#various aspect of cellular mechanisms. To isolate individual#N#cells in live imaging data,  introduce an elegant image segmentation#N#framework that effectively extracts cell boundaries,#N#even in the presence of poor edge details. Our approach works#N#in two stages. First,  estimate pixel interior/border/exterior#N#class probabilities using random ferns. Then,  use an energy#N#minimization framework to compute boundaries whose#N#localization is compliant with the pixel class probabilities. #N#validate our approach on a manually annotated dataset.
['Arnaud Browet', 'Christophe De Vleeschouwer', 'Laurent Jacques', 'Navrita Mathiah', 'Bechara Saykali', 'Isabelle Migeotte']
I am writing a research paper on a idea CELL SEGMENTATION WITH RANDOM FERNS AND GRAPH-CUTS
[{"from": "human", "value": "I am writing a research paper on a idea CELL SEGMENTATION WITH RANDOM FERNS AND GRAPH-CUTS"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The progress in imaging techniques have allod the study of#N#various aspect of cellular mechanisms. To isolate individual#N#cells in live imaging data,  introduce an elegant image segmentation#N#framework that effectively extracts cell boundaries,#N#even in the presence of poor edge details. Our approach works#N#in two stages. First,  estimate pixel interior/border/exterior#N#class probabilities using random ferns. Then,  use an energy#N#minimization framework to compute boundaries whose#N#localization is compliant with the pixel class probabilities. #N#validate our approach on a manually annotated dataset."}]