Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation

The Dice similarity coefficient (DSC) is both a widely used metric and loss function for biomedical image segmentation due to its robustness to class imbalance. However, it is well known that the DSC loss is poorly calibrated, resulting in overconfident predictions that cannot be usefully interprete...

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Detalles Bibliográficos
Autores principales: Yeung, Michael, Rundo, Leonardo, Nan, Yang, Sala, Evis, Schönlieb, Carola-Bibiane, Yang, Guang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039156/
https://www.ncbi.nlm.nih.gov/pubmed/36474089
http://dx.doi.org/10.1007/s10278-022-00735-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039156/
https://www.ncbi.nlm.nih.gov/pubmed/36474089
http://dx.doi.org/10.1007/s10278-022-00735-3

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