Abstract

Abstract Motivation: Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries. Results: We developed Cytomine to foster active and distributed collaboration of multidisciplinary teams for large-scale image-based studies. It uses web development methodologies and machine learning in order to readily organize, explore, share and analyze (semantically and quantitatively) multi-gigapixel imaging data over the internet. We illustrate how it has been used in several biomedical applications. Availability and implementation: Cytomine (http://www.cytomine.be/) is freely available under an open-source license from http://github.com/cytomine/. A documentation wiki (http://doc.cytomine.be) and a demo server (http://demo.cytomine.be) are also available. Contact: info@cytomine.be Supplementary information: Supplementary data are available at Bioinformatics online.

Keywords

Computer scienceDocumentationLicenseThe InternetWorld Wide WebMIT LicenseOpen sourceMultidisciplinary approachData scienceScale (ratio)SoftwareOperating system

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Publication Info

Year
2016
Type
article
Volume
32
Issue
9
Pages
1395-1401
Citations
189
Access
Closed

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Cite This

Raphaël Marée, Loïc Rollus, Benjamin H. Stevens et al. (2016). Collaborative analysis of multi-gigapixel imaging data using Cytomine. Bioinformatics , 32 (9) , 1395-1401. https://doi.org/10.1093/bioinformatics/btw013

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DOI
10.1093/bioinformatics/btw013