  Correct performance assessment is crucial for evaluating modern artificial
intelligence algorithms in medicine like deep-learning based medical image
segmentation models. However, there is no universal metric library in Python
for standardized and reproducible evaluation. Thus, we propose our open-source
publicly available Python package MISeval: a metric library for Medical Image
Segmentation Evaluation. The implemented metrics can be intuitively used and
easily integrated into any performance assessment pipeline. The package
utilizes modern CI/CD strategies to ensure functionality and stability. MISeval
is available from PyPI (miseval) and GitHub:
https://github.com/frankkramer-lab/miseval.
