AUTHOR=Li Rui , Sharma Vaibhav , Thangamani Subasini , Yakimovich Artur TITLE=Open-Source Biomedical Image Analysis Models: A Meta-Analysis and Continuous Survey JOURNAL=Frontiers in Bioinformatics VOLUME=2 YEAR=2022 URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2022.912809 DOI=10.3389/fbinf.2022.912809 ISSN=2673-7647 ABSTRACT=

Open-source research software has proven indispensable in modern biomedical image analysis. A multitude of open-source platforms drive image analysis pipelines and help disseminate novel analytical approaches and algorithms. Recent advances in machine learning allow for unprecedented improvement in these approaches. However, these novel algorithms come with new requirements in order to remain open source. To understand how these requirements are met, we have collected 50 biomedical image analysis models and performed a meta-analysis of their respective papers, source code, dataset, and trained model parameters. We concluded that while there are many positive trends in openness, only a fraction of all publications makes all necessary elements available to the research community.