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

MISeval: a Metric Library for Medical Image Segmentation Evaluation