Calibration and Bias
A software for evaluating model calibration, volume bias and a correlation between the two
Description:
We provide software to measure per-image expected calibration error (ECE), per-image volume bias (defined as difference between true volume and prediction based on a segmentation system) and the correlation between them.
More Information:
- Grand Challenge/Workpackage(s): GC1 - WP6
- Responsible Research Lead: Matthew B. Blaschko
- Authors: Teodora Popordanoska, Jeroen Bertels, Matthew B. Blaschko
- Programming Language: Python
- Link to the repository
- Categories: Supervised Learning, Images
Publications:
- T. Popordanoska, J. Bertels, D. Vandermeulen, F. Maes, M. Blaschko, "On the relationship between calibrated predictors and unbiased volume estimation", 24th international conference on medical image computing and computer assisted intervention (MICCAI 2021), 2021.
