18 citations · 32 across the 6 of their papers we have counts for
7 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…
Differentiable Deconvolution for Improved Stroke Perfusion Analysis
Ezequiel de la Rosa, David Robben, Diana M. Sima +2
Perfusion imaging is the current gold standard for acute ischemic stroke analysis. It allows quantification of the salvageable and non-salvageable tissue regions (penumbra and core…
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…
Unsupervised 3D Brain Anomaly Detection
Jaime Simarro, Ezequiel de la Rosa, Thijs Vande Vyvere +2
Anomaly detection (AD) is the identification of data samples that do not fit a learned data distribution. As such, AD systems can help physicians to determine the presence, severit…
Improved inter-scanner MS lesion segmentation by adversarial training on longitudinal data
Mattias Billast, Maria Ines Meyer, Diana M. Sima +1
The evaluation of white matter lesion progression is an important biomarker in the follow-up of MS patients and plays a crucial role when deciding the course of treatment. Current…
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…