4 papers · 1 filter
Assessing nnU-Net Generalization across Brain Tumor Populations in BraTS-GoAT 2026
Tristan Kirscher, Vivian Metzger, Philippe Meyer +1
BraTS-GoAT evaluates tumor segmentation across heterogeneous populations. We trained a conventional 3D nnU-Net on 1,351 labeled cases using five-fold cross-validation and 1,000 epo…
Rethinking Post-Hoc Calibration in Semantic Segmentation
Tristan Kirscher, Kim-Celine Kahl, Balint Kovacs +5
Reliable confidence estimates are essential in semantic segmentation, yet modern models often remain miscalibrated. We investigate two overlooked issues in post-hoc calibration. Fi…
Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation
Tristan Kirscher, Markus Bujotzek, Yannick Kirchhoff +5
Ensemble disagreement is widely used as a proxy for epistemic uncertainty in medical image segmentation. In practice, many studies form ensembles via K-fold cross-validation (CV),…
Assessing Pancreatic Ductal Adenocarcinoma Vascular Invasion: the PDACVI Benchmark
M. Riera-Marín, O. K. Sikha, J. Rodríguez-Comas +23
Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC), and eligibility depends on accurate assessment of vascular invasion…