18 citations · 32 across the 6 of their papers we have counts for
3 papers · 1 filter
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…