Developing open-source software for bioimage analysis: opportunities and challenges

Florian Levet, Anne E. Carpenter, Kevin W. Eliceiri, Anna Kreshuk, Peter Bankhead, Robert Haase
F1000Res. 2021-04-19; 10: 302
DOI: 10.12688/f1000research.52531.1

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Fast-paced innovations in imaging have resulted in single systems producing exponential amounts of data to be analyzed. Computational methods developed in computer science labs have proven to be crucial for analyzing these data in an unbiased and efficient manner, reaching a prominent role in most microscopy studies. Still, their use usually requires expertise in bioimage analysis, and their accessibility for life scientists has therefore become a bottleneck. Open-source software for bioimage analysis has developed to disseminate these computational methods to a wider audience, and to life scientists in particular. In recent years, the influence of many open-source tools has grown tremendously, helping tens of thousands of life scientists in the process. As creators of successful open-source bioimage analysis software, we here discuss the motivations that can initiate development of a new tool, the common challenges faced, and the characteristics required for achieving success.

Auteurs Bordeaux Neurocampus