seg-metrics: a Python package to compute segmentation metrics

Medical image segmentation (MIS) is an important task in medical image processing. Unfortunately, there is not a out-of-the-box python package for the evaluation metrics of MIS. Therefore, we developed seg-metrics, an open-source Python package for MIS model evaluation. Unlike existing packages, seg-metrics offers user-friendly interfaces for various overlap-based and distance-based metrics, providing a comprehensive solution. seg-metrics supports multiple file formats and is easily installable through the Python Package Index (PyPI). With a focus on speed and convenience, seg-metrics stands as a valuable tool for efficient MIS model assessment. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by the China Scholarship Council No.202007720110. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors