Author

C. Gani

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Open access Oct 2026

Uncertainty-aware auto-segmentation enables adaptive radiotherapy planning of liver metastases.

PURPOSE Despite remarkable auto-segmentation performance and growing clinical adoption, models frequently fail to generalize beyond the training distribution. Therefore, this study aimed to develop and validate an uncertainty-aware segmentation pipeline that yields high delineation accuracy for liver cancer patients an...

D. Langner, C. Gani, S. Boeke et al. · Radiotherapy and Oncology · 0 citations

Open access Aug 2026

Uncertainty estimation for reliable neural network-based radiotherapy dose modelling using Monte Carlo dropout, mean variance estimation and deep ensemble

All methods provided meaningful uncertainty estimates clearly associated with prediction error, and MVE showed the lowest ENCE and strongest correlation with MAE while requiring the least computation.

Moritz Schneider, T. Eberhardt, C. Gani et al. · Physics and Imaging in Radia... · 0 citations