Entropy of a Bayesian network trained on sparse point labels is proportional to nucleus probability, enabling weakly supervised nuclei detection that reaches 0.724 mAP50 versus 0.834 for fully supervised training.
Split and merge watershed: A two-step method for cell segmentation in fluorescence microscopy images
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Entropy Bootstrapping for Weakly Supervised Nuclei Detection
Entropy of a Bayesian network trained on sparse point labels is proportional to nucleus probability, enabling weakly supervised nuclei detection that reaches 0.724 mAP50 versus 0.834 for fully supervised training.