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arXiv Computer Vision By Riya Deepak Shet, Chenxi Liang, Le Zhang

Reliability analysis for BraTS-GoAT segmentation: a controlled robustness study of deep-ensemble uncertainty

Read the original on arXiv Computer Vision →

The study evaluates the reliability of deep‑ensemble uncertainty for brain tumour segmentation on the BraTS‑GoAT dataset. A 5‑fold cross‑validated nnU‑Net baseline and a 3‑seed deep ensemble were compared for calibration and error detection; the ensemble showed modest gains in calibration on in‑distribution data but the single model’s confidence remained flat while accuracy degraded under synthetic corruptions. Disagreement among ensemble members rose sharply with corruption severity, proving to be a more sensitive indicator of acquisition shift than single‑model confidence.

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