activity
20222025
most citedAutomated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Medical Imaging AI Competitions Lack Fairness

Annika Reinke, Evangelia Christodoulou, Sthuthi Sadananda +34

Benchmarking competitions are central to the development of artificial intelligence (AI) in medical imaging, defining performance standards and shaping methodological progress. How…

cs.CV2025

False Promises in Medical Imaging AI? Assessing Validity of Outperformance Claims

Evangelia Christodoulou, Annika Reinke, Pascaline Andrè +23

Performance comparisons are fundamental in medical imaging Artificial Intelligence (AI) research, often driving claims of superiority based on relative improvements in common perfo…

cs.CV2024

Confidence intervals uncovered: Are we ready for real-world medical imaging AI?

Evangelia Christodoulou, Annika Reinke, Rola Houhou +19

Medical imaging is spearheading the AI transformation of healthcare. Performance reporting is key to determine which methods should be translated into clinical practice. Frequently…

eess.IV20242 cited

Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation

Sophie Loizillon, Simona Bottani, Stéphane Mabille +6

The emergence of clinical data warehouses (CDWs), which contain the medical data of millions of patients, has paved the way for vast data sharing for research. The quality of MRIs…

eess.IV20221 cited

Fourier Disentangled Multimodal Prior Knowledge Fusion for Red Nucleus Segmentation in Brain MRI

Guanghui Fu, Gabriel Jimenez, Sophie Loizillon +9

Early and accurate diagnosis of parkinsonian syndromes is critical to provide appropriate care to patients and for inclusion in therapeutic trials. The red nucleus is a structure o…