469 citations
- Université de RennesFR13 papers
- InsermFR10 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Imperial College LondonGB4 papers
- Laboratoire Traitement et Communication de l’InformationFR4 papers
- Statistics BelgiumBE4 papers
- Universitat Pompeu FabraES4 papers
- Centre de Recherche en Acquisition et Traitement de l'Image pour la SantéFR3 papers
- Centre Hospitalier Universitaire de RennesFR3 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE3 papers
- King's College LondonGB3 papers
- University College LondonGB3 papers
31 papers
KonfAI: A Modular and Fully Configurable Framework for Deep Learning in Medical Imaging
Valentin Boussot, Jean-Louis Dillenseger
KonfAI is a modular, extensible, and fully configurable deep learning framework specifically designed for medical imaging tasks. It enables users to define complete training, infer…
Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results
Meritxell Riera-Marin, Sikha O K, Julia Rodriguez-Comas +29
Deep learning (DL) has become the dominant approach for medical image segmentation, yet ensuring the reliability and clinical applicability of these models requires addressing key…
Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate
Leonardo Geronzi, Antonio Martinez, Michel Rochette +13
Objective: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to pre…
CroissantLLM: A Truly Bilingual French-English Language Model
Manuel Faysse, Patrick Fernandes, Nuno M. Guerreiro +13
We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully op…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Comparison between an exact and a heuristic neural mass model with second order synapses
Pau Clusella, Elif Köksal-Ersöz, Jordi Garcia-Ojalvo +1
Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal populations. A common framework for NMMs assumes heuristically that the output firing rate o…