429 citations · 773 across the 12 of their papers we have counts for
8 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…
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…
Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling
Balder Croquet, Daan Christiaens, Seth M. Weinberg +3
Registration is an essential tool in image analysis. Deep learning based alternatives have recently become popular, achieving competitive performance at a faster speed. However, ma…
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…
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…
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
Sofie Tilborghs, Ine Dirks, Lucas Fidon +19
Recent research on COVID-19 suggests that CT imaging provides useful information to assess disease progression and assist diagnosis, in addition to help understanding the disease.…