Publications (19)
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.…
DeepVoxNet2: Yet another CNN framework
Jeroen Bertels, David Robben, Robin Lemmens +1
We know that both the CNN mapping function and the sampling scheme are of paramount importance for CNN-based image analysis. It is clear that both functions operate in the same spa…
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…
ISLES'24 -- A Real-World Longitudinal Multimodal Stroke Dataset
Evamaria Olga Riedel, Ezequiel de la Rosa, The Anh Baran +18
Stroke remains a leading cause of global morbidity and mortality, imposing a heavy socioeconomic burden. Advances in endovascular reperfusion therapy and CT and MR imaging for trea…
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…
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…