17 citations · 26 across the 8 of their papers we have counts for
4 papers · 1 filter
Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solution
Theophraste Henry, Alexandre Carre, Marvin Lerousseau +4
Brain tumor segmentation is a critical task for patient's disease management. In order to automate and standardize this task, we trained multiple U-net like neural networks, mainly…
Multimodal brain tumor classification
Marvin Lerousseau, Eric Deutsh, Nikos Paragios
Cancer is a complex disease that provides various types of information depending on the scale of observation. While most tumor diagnostics are performed by observing histopathologi…
AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia
Guillaume Chassagnon, Maria Vakalopoulou, Enzo Battistella +28
Chest computed tomography (CT) is widely used for the management of Coronavirus disease 2019 (COVID-19) pneumonia because of its availability and rapidity. The standard of referenc…
Weakly supervised multiple instance learning histopathological tumor segmentation
Marvin Lerousseau, Maria Vakalopoulou, Marion Classe +7
Histopathological image segmentation is a challenging and important topic in medical imaging with tremendous potential impact in clinical practice. State of the art methods rely on…