5 citations · 7 across the 2 of their papers we have counts for
7 papers
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…
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…
Detection of vertebral fractures in CT using 3D Convolutional Neural Networks
Joeri Nicolaes, Steven Raeymaeckers, David Robben +4
Osteoporosis induced fractures occur worldwide about every 3 seconds. Vertebral compression fractures are early signs of the disease and considered risk predictors for secondary os…
Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning
David Robben, Anna M. M. Boers, Henk A. Marquering +9
CT Perfusion (CTP) imaging has gained importance in the diagnosis of acute stroke. Conventional perfusion analysis performs a deconvolution of the measurements and thresholds the p…