429 citations · 454 across the 6 of their papers we have counts for
5 papers · 1 filter
Final infarct prediction in acute ischemic stroke
Jeroen Bertels, David Robben, Dirk Vandermeulen +1
This article focuses on the control center of each human body: the brain. We will point out the pivotal role of the cerebral vasculature and how its complex mechanisms may vary bet…
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging
Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky +37
Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised c…
Post Training Uncertainty Calibration of Deep Networks For Medical Image Segmentation
Axel-Jan Rousseau, Thijs Becker, Jeroen Bertels +2
Neural networks for automated image segmentation are typically trained to achieve maximum accuracy, while less attention has been given to the calibration of their confidence score…
Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index
Tom Eelbode, Jeroen Bertels, Maxim Berman +4
In many medical imaging and classical computer vision tasks, the Dice score and Jaccard index are used to evaluate the segmentation performance. Despite the existence and great emp…
Optimization with soft Dice can lead to a volumetric bias
Jeroen Bertels, David Robben, Dirk Vandermeulen +1
Segmentation is a fundamental task in medical image analysis. The clinical interest is often to measure the volume of a structure. To evaluate and compare segmentation methods, the…