VitaminP uses paired H&E-mIF data to train a model that transfers molecular boundary information, enabling accurate whole-cell segmentation directly from routine H&E histology across 34 cancer types.
Segmentation of nuclei in histopathology images by deep regression of the distance map.IEEE Transactions on Medical Imaging, 38(2):448–459
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
NucEval is a unified evaluation framework for nuclear instance segmentation that modifies standard metrics to handle vague regions, normalize scores, manage overlaps, and account for border uncertainty.
citing papers explorer
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VitaminP: cross-modal learning enables whole-cell segmentation from routine histology
VitaminP uses paired H&E-mIF data to train a model that transfers molecular boundary information, enabling accurate whole-cell segmentation directly from routine H&E histology across 34 cancer types.
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NucEval: A Robust Evaluation Framework for Nuclear Instance Segmentation
NucEval is a unified evaluation framework for nuclear instance segmentation that modifies standard metrics to handle vague regions, normalize scores, manage overlaps, and account for border uncertainty.