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Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl
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.
Weakly Supervised Learning of Single-Cell Feature Embeddings
Many new applications in drug discovery and functional genomics require capturing the morphology of individual imaged cells as comprehensively as possible rather than measuring one particular feature.
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