activity
20162023
most citedAttention U-Net: Learning Where to Look for the Pancreas

4.6k citations · 14.9k across the 210 of their papers we have counts for

collaborators

217 papers

eess.IV2023

Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images

Chinmay Prabhakar, Hongwei Bran Li, Johannes C. Paetzold +6

Multiple Sclerosis (MS) is a severe neurological disease characterized by inflammatory lesions in the central nervous system. Hence, predicting inflammatory disease activity is cru…

eess.IV2023

Bias in Unsupervised Anomaly Detection in Brain MRI

Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler +3

Unsupervised anomaly detection methods offer a promising and flexible alternative to supervised approaches, holding the potential to revolutionize medical scan analysis and enhance…

eess.IV2023

The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning

Denis Prokopenko, Kerstin Hammernik, Thomas Roberts +3

Dynamic free-breathing fetal cardiac MRI is one of the most challenging modalities, which requires high temporal and spatial resolution to depict rapid changes in a small fetal hea…

eess.IV2023★ 7 cited

Using UK Biobank data to establish population-specific atlases from whole body MRI

Sophie Starck, Vasiliki Sideri-Lampretsa, Jessica J. M. Ritter +4

Reliable reference data in medical imaging is largely unavailable. Developing tools that allow for the comparison of individual patient data to reference data has a high potential…

eess.SP2023★ 1 cited

Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging

Özgün Turgut, Philip Müller, Paul Hager +5

Cardiovascular diseases (CVD) can be diagnosed using various diagnostic modalities. The electrocardiogram (ECG) is a cost-effective and widely available diagnostic aid that provide…

eess.IV2023

Spatio-Temporal Encoding of Brain Dynamics with Surface Masked Autoencoders

Simon Dahan, Logan Z. J. Williams, Yourong Guo +2

The development of robust and generalisable models for encoding the spatio-temporal dynamics of human brain activity is crucial for advancing neuroscientific discoveries. However,…