Seg-metrics: a Python package to compute segmentation metrics

Jingnan Jia, Marius Staring, Berend C. Stoel
1/12/2024
cs.CVcs.AI

No official code found. Best implementation: Jingnan-Jia/segmentation_metrics (188 stars, MIT, last commit 2024-07-16).

Abstract

In response to a concerning trend of selectively emphasizing metrics in medical image segmentation (MIS) studies, we introduce \texttt{seg-metrics}, an open-source Python package for standardized MIS model evaluation. Unlike existing packages, \texttt{seg-metrics} offers user-friendly interfaces for various overlap-based and distance-based metrics, providing a comprehensive solution. \texttt{seg-metrics} supports multiple file formats and is easily installable through the Python Package Index (PyPI). With a focus on speed and convenience, \texttt{seg-metrics} stands as a valuable tool for efficient MIS model assessment.

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Code Implementations(1)

Jingnan-Jia/segmentation_metricsCommunity100%
MIT

A package to compute medical segmentation metrics.

18813PythonJun 17, 20202 years agoMIT
dicehausdorff-distancejaccard-similaritymedical-imagingmetrics+2 more

Cite this paper

@article{jia2024segmetrics,
  title  = {Seg-metrics: a Python package to compute segmentation metrics},
  author = {Jingnan Jia and Marius Staring and Berend C. Stoel},
  year   = {2024},
  eprint = {2403.07884},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.07884v1}
}

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