Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl
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Abstract
Segmenting the nuclei of cells in microscopy images is often the first step in the quantitative analysis of imaging data for biological and biomedical applications. Many bioimage analysis tools can segment nuclei in images but need to be selected and configured for every experiment. The 2018 Data Science Bowl attracted 3,891 teams worldwide to make the first attempt to build a segmentation method that could be applied to any two-dimensional light microscopy image of stained nuclei across experiments, with no human interaction. Top participants in the challenge succeeded in this task, developing deep-learning-based models that identified cell nuclei across many image types and experimental conditions without…
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Keywords
- Segmentation
- Computer science
- Artificial intelligence
- Software
- Task (project management)
- Image segmentation
- Deep learning
- Market segmentation
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