- OPG-Based Dental Age Estimation Using a Data-Technical Exploration of Deep Learning Techniques(2024)
Auteurs: Peter Claes, Dirk Vandermeulen, Patrick Thevissen, Jeroen Bertels
- USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging(2023)
Auteurs: Jeroen Bertels
- Reversibility of Diffusion-Weighted Imaging Lesions in Patients With Ischemic Stroke in the WAKE-UP Trial(2023)
Auteurs: Anke Wouters, Jeroen Bertels, Patrick Dupont, Robin Lemmens
Pagina's: 1560 - 1568
- Understanding Final Infarct Prediction in Acute Ischemic Stroke Using Convolutional Neural Networks(2022)
Auteurs: Jeroen Bertels, Dirk Vandermeulen, David Robben
- Deep learning-based dental implant recognition using synthetic X-ray images(2022)
Auteurs: Jeroen Bertels, Dirk Vandermeulen
- The Dice loss in the context of missing or empty labels: introducing phi and epsilon(2022)
Auteurs: Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen, Frederik Maes
Pagina's: 527 - 537
Aantal pagina's: 11
- Cross-modal distillation to improve MRI-based brain tumor segmentation with missing MRI sequences.(2021)
Auteurs: Masoomeh Rahimpour, Jeroen Bertels, Ahmed Radwan, Stefan Sunaert, Dirk Vandermeulen, Frederik Maes, Karolien Goffin, Michel Koole
Pagina's: 1 - 12
- Post training uncertainty calibration of deep networks for medical image segmentation(2021)
Auteurs: Jeroen Bertels, Matthew Blaschko
Pagina's: 1052 - 1056
- On the relationship between calibrated predictors and unbiased volume estimation(2021)
Auteurs: Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew Blaschko
Pagina's: 678 - 688
- Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty(2021)
Auteurs: Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens
