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Deep learning identifies morphological patterns of homologous recombination deficiency in luminal breast cancers from whole slide images

Tristan Lazard , Guillaume Bataillon , Peter Naylor , Tatiana Popova , François-Clément Bidard et al.
Cell Reports Medicine, 2022, 3 (12), pp.100872. ⟨10.1016/j.xcrm.2022.100872⟩
Journal articles hal-03936608v1

Neural network for the prediction of treatment response in Triple Negative Breast Cancer *

Peter Naylor , Tristan Lazard , Guillaume Bataillon , Marick Lae , Anne Vincent-Salomon et al.
2022
Preprints, Working Papers, ... hal-03633354v1
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Predicting Residual Cancer Burden in a triple negative breast cancer cohort

Peter Naylor , Joseph Boyd , Marick Lae , Fabien Reyal , Thomas Walter et al.
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI), Apr 2019, Venice, Italy. pp.933-937, ⟨10.1109/ISBI.2019.8759205⟩
Conference papers hal-02440647v1

Nuclei segmentation in histopathology images using deep neural networks

Peter Naylor , Marik Laé , Fabien Reyal , Thomas Walter
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017, Melbourne, Australia
Conference papers hal-01683969v1

Segmentation of Nuclei in Histopathology Images by deep regression of the distance map

Peter Naylor , Marick Lae , Fabien Reyal , Thomas Walter
IEEE Transactions on Medical Imaging, 2018, pp.1-12
Journal articles hal-01984033v1