469 citations
- Université de RennesFR22 papers
- InsermFR18 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- Université Rennes 1FR5 papers
- Centre Hospitalier Universitaire de RennesFR4 papers
- Imperial College LondonGB4 papers
- Laboratoire Traitement et Communication de l’InformationFR4 papers
- Statistics BelgiumBE4 papers
- Universitat Pompeu FabraES4 papers
- University College LondonGB4 papers
- Centre de Recherche en Acquisition et Traitement de l'Image pour la SantéFR3 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE3 papers
11 papers · 1 filter
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…
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…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images
Yuting He, Tiantian Li, Guanyu Yang +6
Deep learning-based medical image registration and segmentation joint models utilize the complementarity (augmentation data or weakly supervised data from registration, region cons…
Fractional Wavelet Scattering Network and Applications
Li Liu, Jiasong Wu, Dengwang Li +2
Objective: The present study introduces a fractional wavelet scattering network (FrScatNet), which is a generalized translation invariant version of the classical wavelet scatterin…