{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T06:19:59Z","timestamp":1757312399212},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,25]]},"abstract":"<jats:p>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 DevOps strategies to ensure functionality and stability. MISeval is available from PyPI (miseval) and GitHub: https:\/\/github.com\/frankkramer-lab\/miseval.<\/jats:p>","DOI":"10.3233\/shti220391","type":"book-chapter","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:12:34Z","timestamp":1653480754000},"source":"Crossref","is-referenced-by-count":13,"title":["MISeval: A Metric Library for Medical Image Segmentation Evaluation"],"prefix":"10.3233","author":[{"given":"Dominik","family":"M\u00fcller","sequence":"first","affiliation":[{"name":"IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany"},{"name":"Medical Data Integration Center, Institute for Digital Medicine, University Hospital Augsburg, Germany"}]},{"given":"Dennis","family":"Hartmann","sequence":"additional","affiliation":[{"name":"IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany"}]},{"given":"Philip","family":"Meyer","sequence":"additional","affiliation":[{"name":"IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany"},{"name":"Medical Data Integration Center, Institute for Digital Medicine, University Hospital Augsburg, Germany"}]},{"given":"Florian","family":"Auer","sequence":"additional","affiliation":[{"name":"IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany"}]},{"given":"I\u00f1aki","family":"Soto-Rey","sequence":"additional","affiliation":[{"name":"Medical Data Integration Center, Institute for Digital Medicine, University Hospital Augsburg, Germany"}]},{"given":"Frank","family":"Kramer","sequence":"additional","affiliation":[{"name":"IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Challenges of Trustable AI and Added-Value on Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220391","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:12:35Z","timestamp":1653480755000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220391"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,25]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220391","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,25]]}}}