17 citations · 20 across the 2 of their papers we have counts for
4 papers · 1 filter
Exploring Deep Registration Latent Spaces
Théo Estienne, Maria Vakalopoulou, Stergios Christodoulidis +8
Explainability of deep neural networks is one of the most challenging and interesting problems in the field. In this study, we investigate the topic focusing on the interpretabilit…
Deep learning based registration using spatial gradients and noisy segmentation labels
Théo Estienne, Maria Vakalopoulou, Enzo Battistella +6
Image registration is one of the most challenging problems in medical image analysis. In the recent years, deep learning based approaches became quite popular, providing fast and p…
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…
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritum…