Cytomine is, to the best of our knowledge, the first open-source rich internet application to enable highly collaborative and multidisciplinary analysis of multi-gigapixel imaging data.

Build at University of Liège, Cytomine supports both remote visualization, collaborative semantic annotation, and semi-automated analysis through the web, making it an ideal tool for collaborative research, teaching and diagnosis in every large-image related topics.

Its design was driven by life science and bioimage informatics research needs: software versatility, interoperability, modularity and extensibility, image recognition tailored via learning from ground-truth data and proofreading tools, reproducible research, and data accessibility and reusability.

It is being used for years by our collaborators working with large sets of bioimages in numerous domains including cancer research, development, and toxicology, and is now adapted for pedagogical purposes.

Overall, we believe Cytomine is an important new tool of broad interest to foster active communication and distributed collaboration between life, computer and citizen scientists, but also physicians, teachers and students, in an unprecedented way using machine learning and web communication mechanisms.

Full documentation can be found online.

See our Cytomine-bootstrap project to install it with Docker

Check how to install a development environment for Cytomine.

When using our software, we kindly ask you to cite our website url and related publications in all your work (publications, studies, oral presentations,...). In particular, we recommend to cite (Marée et al., Bioinformatics 2016) paper, and to use our logo when appropriate. See our license files for additional details.

• URL: http://www.cytomine.org/
• Logo: Available here
• Scientific paper: Raphaël Marée, Loïc Rollus, Benjamin Stévens, Renaud Hoyoux, Gilles Louppe, Rémy Vandaele, Jean-Michel Begon, Philipp Kainz, Pierre Geurts and Louis Wehenkel. Collaborative analysis of multi-gigapixel imaging data using Cytomine, Bioinformatics, DOI: 10.1093/bioinformatics/btw013, 2016.

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