6 citations · 11 across the 3 of their papers we have counts for
3 papers
Convolutional neural networks for medical image segmentation
Jeroen Bertels, David Robben, Robin Lemmens +1
In this article, we look into some essential aspects of convolutional neural networks (CNNs) with the focus on medical image segmentation. First, we discuss the CNN architecture, t…
The Dice loss in the context of missing or empty labels: Introducing and
Sofie Tilborghs, Jeroen Bertels, David Robben +2
Albeit the Dice loss is one of the dominant loss functions in medical image segmentation, most research omits a closer look at its derivative, i.e. the real motor of the optimizati…
On the relationship between calibrated predictors and unbiased volume estimation
Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen +2
Machine learning driven medical image segmentation has become standard in medical image analysis. However, deep learning models are prone to overconfident predictions. This has led…