Dear colleagues, After five years of research and development at the University of Liège, Belgium, I would like to draw your attention to the release under an open source licence of our Cytomine software (http://www.cytomine.be/) for collaborative analysis of multi-gigapixel imaging data. Although our initial focus was on biomedical research with cytology and histology whole-slide images, this is a generic software that might be useful for other types of imaging data from various fields (e.g. botany, geology, astronomy, environmental biology, ...). Based on modern web, database, and machine learning algorithms, it has been designed to foster active and distributed collaboration between computer vision/machine learning researchers and other scientists dealing with very large images. Among other functionalities, it implements: - a web user interface to explore (à la Google Maps) very large images using pyramidal formats; - web user interfaces to efficiently and collaboratively build large semantic ground-truth datasets from multi-gigapixel images; - a multi-thread implementation of our tree-based learning recognition algorithms (for content-based image retrieval [MIR2010], object classification [PatternRecognitionLetters2016], image segmentation [VISAPP2009], and landmark detection; - web proofreading tools to edit (ours or yours) algorithm predictions; - a RESTful API and software templating mechanisms to easily import/export data with your own software and extend it to your own purposes; - Python and Java clients to easily access and extend the system. Our paper in Bioinformatics (open access): http://bioinformatics.oxfordjournals.org/content/early/2016/01/09/bioinforma... Other related papers: http://www.cytomine.be/#publications Read more (documentation, source code, etc.) on: http://www.cytomine.be/ Best regards, Raphaël. -- Raphaël Marée (PhD) http://www.montefiore.ulg.ac.be/~maree/ http://www.cytomine.be/ Tél.: +32 4 366 26 44 | Fax: +32 4 366 29 84