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Chair of Computer Science 5 (Pattern Recognition)
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Dept. of Computer Sc. » Pattern Recognition » Our Team » Aubreville, Marc » Source Code

Dipl.-Ing. Marc Aubreville

Researcher in the Computer Vision (CV) group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

SlideRunner

SlideRunner is an open source tool for massive cell annotations in whole slide histology images.

It has been created in close cooperation between the Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg and the Institute of Veterenary Pathology, Freie Universität Berlin.

All details can be found on the project's github page at:

Opens external link in new window https://github.com/maubreville/SlideRunner

A preprint of the paper describing the project can be found on arXiv Opens external link in new window link.

Patch-based Carcinoma Classification on Confocal Laser Endomicroscopy Images

At the moment, you can find the source code of the patch-based approach we described in the Scientific Reports (Nature Publishing Group) paper:

Opens external link in new window Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning

The code and according description can be found Opens internal link in current window here.



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Department of Computer Science 5 Our Team Aubreville, Marc Projects Source Code CLE Carcinoma Detection Publications Thesis Curriculum Vitae Research Publications Free Software Data Courses Curriculum Theses Press Releases Cooperations Open Positions LME Videos Ph.D. Gallery Contact Intranet Impressum Datenschutzerklärung Contact +49 9131 85 27891 +49 9131 85 27270 09.157 Address Universität Erlangen-Nürnberg Chair of Computer Science 5 (Pattern Recognition) Martensstr. 3 91058 Erlangen Germany Driving directions Powered by	Dept. of Computer Sc. » Pattern Recognition » Our Team » Aubreville, Marc » Source Code Dipl.-Ing. Marc Aubreville Researcher in the Computer Vision (CV) group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg SlideRunner SlideRunner is an open source tool for massive cell annotations in whole slide histology images. It has been created in close cooperation between the Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg and the Institute of Veterenary Pathology, Freie Universität Berlin. All details can be found on the project's github page at: https://github.com/maubreville/SlideRunner A preprint of the paper describing the project can be found on arXiv link. Patch-based Carcinoma Classification on Confocal Laser Endomicroscopy Images At the moment, you can find the source code of the patch-based approach we described in the Scientific Reports (Nature Publishing Group) paper: Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning The code and according description can be found here.