2 citations · 3 across the 3 of their papers we have counts for
3 papers
Deep Unsupervised Anomaly Detection in Brain Imaging: Large-Scale Benchmarking and Bias Analysis
Alexander Frotscher, Christian F. Baumgartner, Thomas Wolfers
Deep unsupervised anomaly detection in brain magnetic resonance imaging offers a promising route to identify pathological deviations without requiring lesion-specific annotations.…
MRExtrap: Longitudinal Aging of Brain MRIs using Linear Modeling in Latent Space
Jaivardhan Kapoor, Jakob H. Macke, Christian F. Baumgartner
Simulating aging in 3D brain MRI scans can reveal disease progression patterns in neurological disorders such as Alzheimer's disease. Current deep learning-based generative models…
Unsupervised Anomaly Detection using Aggregated Normative Diffusion
Alexander Frotscher, Jaivardhan Kapoor, Thomas Wolfers +1
Early detection of anomalies in medical images such as brain MRI is highly relevant for diagnosis and treatment of many conditions. Supervised machine learning methods are limited…