K-fold CV ensembles and deep ensembles produce distinct uncertainty behaviors, with deep ensembles improving calibration and failure detection while CV ensembles correlate more with inter-rater variability.
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A radiomic-guided subtyping and lesion-wise ensemble pipeline delivers segmentation performance comparable to top entries on diverse BraTS 2025 brain tumor datasets.
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Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation
K-fold CV ensembles and deep ensembles produce distinct uncertainty behaviors, with deep ensembles improving calibration and failure detection while CV ensembles correlate more with inter-rater variability.
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Adaptable Segmentation Pipeline for Diverse Brain Tumors with Radiomic-guided Subtyping and Lesion-Wise Model Ensemble
A radiomic-guided subtyping and lesion-wise ensemble pipeline delivers segmentation performance comparable to top entries on diverse BraTS 2025 brain tumor datasets.