A ConvNeXt ensemble achieves 84% balanced accuracy on MIDOG25 atypical mitotic figure classification, while a rule-based refinement module trades sensitivity for specificity.
Improving mitotic cell counting accuracy and efficiency using phosphohistone-H3 (PHH3) antibody counterstained with haematoxylin and eosin as part of breast cancer grading,
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Classifying Mitotic Figures in the MIDOG25 Challenge with Deep Ensemble Learning and Rule Based Refinement
A ConvNeXt ensemble achieves 84% balanced accuracy on MIDOG25 atypical mitotic figure classification, while a rule-based refinement module trades sensitivity for specificity.