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Open-Source Biomedical Image Analysis Models: a Meta-analysis and Continuous Survey

Li, R.; Sharma, V.; Thangamani, S.; Yakimovich, A.


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 meta-analysis of their respective paper, 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.

Keywords: deep learning; machine learning; bioimage analysis; open source

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