Medizinische Universität Graz - Research portal
Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab Microb
Marée, R; Rollus, L; Stévens, B; Hoyoux, R; Louppe, G; Vandaele, R; Begon, JM; Kainz, P; Geurts, P; Wehenkel, L.
Collaborative analysis of multi-gigapixel imaging data using Cytomine.
Bioinformatics. 2016; 32(9):1395-1401
Doi: 10.1093/bioinformatics/btw013
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- Co-authors Med Uni Graz
- Kainz Philipp
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- Abstract:
- Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries. 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. 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. info@cytomine.be Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
- Find related publications in this database (using NLM MeSH Indexing)
- Image Interpretation, Computer-Assisted -
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