4 papers
Chronological Contrastive Learning: Few-Shot Progression Assessment in Irreversible Diseases
Clemens Watzenböck, Daniel Aletaha, Michaël Deman +9
Quantitative disease severity scoring in medical imaging is costly, time-consuming, and subject to inter-reader variability. At the same time, clinical archives contain far more lo…
WALINET: A water and lipid identification convolutional Neural Network for nuisance signal removal in 1H MR Spectroscopic Imaging
Paul Weiser, Georg Langs, Stanislav Motyka +5
Purpose. Proton Magnetic Resonance Spectroscopic Imaging (1H-MRSI) provides non-invasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain 1H-M…
Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging
Paul Weiser, Georg Langs, Wolfgang Bogner +11
Introduction: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonanc…
No Modality Left Behind: Dynamic Model Generation for Incomplete Medical Data
Christoph Fürböck, Paul Weiser, Branko Mitic +3
In real world clinical environments, training and applying deep learning models on multi-modal medical imaging data often struggles with partially incomplete data. Standard approac…