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2020 – today
- 2020
[b1]Arnaud Abreu:
Réseaux neuronaux convolutifs profonds et représentations hiérarchiques: applications et perspectives pour la pathologie numérique. (Deep convolutional neural networks and hierarchical representations: applications and perspectives for digital pathology). University of Strasbourg, France, 2020- [j1]Charlotte Syrykh
, Arnaud Abreu, Nadia Amara, Aurore Siegfried, Véronique Maisongrosse, François X. Frenois, Laurent Martin, Cédric Rossi, Camille Laurent, Pierre Brousset:
Accurate diagnosis of lymphoma on whole-slide histopathology images using deep learning. npj Digit. Medicine 3 (2020)
2010 – 2019
- 2019
- [c3]Arnaud Abreu, Camille Franchet, François-Xavier Frenois, Pierre Brousset, Jean-Philippe Girard, Patrice Denéfle, Benoît Naegel, Cédric Wemmert:
Ensemble Of Neural Networks For High Endothelial Venules Detection In Meca-79 Immunohistochemistry Images. ISBI 2019: 938-942 - 2018
- [c2]Arnaud Abreu, François-Xavier Frenois, Salvatore Valitutti, Pierre Brousset, Patrice Denéfle, Benoît Naegel, Cédric Wemmert:
Model-based graph segmentation in 2-D fluorescence microsecopy images. ICPR 2018: 3844-3849 - 2017
- [c1]Arnaud Abreu, François-Xavier Frenois, Salvatore Valitutti, Pierre Brousset, Patrice Denéfle, Benoît Naegel, Cédric Wemmert:
Optimal cut in minimum spanning trees for 3-D cell nuclei segmentation. ISPA 2017: 195-199
Coauthor Index
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