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2020 – today
- 2024
[i3]Mehdi Ounissi, Ilias Sarbout, Jean-Pierre Hugot, Christine Martinez-Vinson, Dominique Berrebi, Daniel Racoceanu:
Scalable, Trustworthy Generative Model for Virtual Multi-Staining from H&E Whole Slide Images. CoRR abs/2407.00098 (2024)- 2023
- [c3]J. Arslan, Mehdi Ounissi, H. Luo, M. Lacroix, P. Dupré, P. Kumar, Arran Hodgkinson, S. Dandou, Romain M. Larive, C. Pignodel, L. Le Cam, Ovidiu Radulescu, Daniel Racoceanu:
Efficient 3D reconstruction of whole slide images in melanoma. Digital and Computational Pathology 2023 - [i2]Gabriel Jimenez, Anuradha Kar, Mehdi Ounissi, Léa Ingrassia, Susana Boluda, Benoît Delatour, Lev Stimmer, Daniel Racoceanu:
Visual deep learning-based explanation for neuritic plaques segmentation in Alzheimer's Disease using weakly annotated whole slide histopathological images. CoRR abs/2302.08511 (2023) - [i1]Mehdi Ounissi, Morwena Latouche, Daniel Racoceanu:
Phagocytosis Unveiled: A Scalable and Interpretable Deep learning Framework for Neurodegenerative Disease Analysis. CoRR abs/2304.13764 (2023) - 2022
- [c2]Gabriel Jimenez
, Anuradha Kar, Mehdi Ounissi, Léa Ingrassia, Susana Boluda, Benoît Delatour, Lev Stimmer, Daniel Racoceanu:
Visual Deep Learning-Based Explanation for Neuritic Plaques Segmentation in Alzheimer's Disease Using Weakly Annotated Whole Slide Histopathological Images. MICCAI (2) 2022: 336-344 - [c1]Kristyna Manousková, Valentin Abadie, Mehdi Ounissi, Gabriel Jimenez, Lev Stimmer, Benoît Delatour, Stanley Durrleman, Daniel Racoceanu:
Tau protein discrete aggregates in Alzheimer's disease: neuritic plaques and tangles detection and segmentation using computational histopathology. Digital and Computational Pathology 2022
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