Publications

Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening

Moving beyond hyperintensity thresholding. This paper analyzes the challenges and outlines opportunities for advancing the field of unsupervised anomaly detection.

Cosmin I. Bercea, Benedikt Wiestler, Daniel Rückert, Julia A Schnabel

Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening

Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection

Generative netowrks to reverse anomalies in medical imaging.

Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia Schnabel

Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection

Federated Disentangled Representation Learning for Unsupervised Brain Anomaly Detection

Implicit disentanglement of shape and appearance with federated learning for unsupervised brain pathology segmentation.

Cosmin I. Bercea, Benedikt Wiestler, Daniel Rückert, Shadi Albarqouni

Federated Disentangled Representation Learning for Unsupervised Brain Anomaly Detection

What do we learn? Debunking the Myth of Unsupervised Outlier Detection

Novel deformable auto-encoders for unsupervised outlier detection

Cosmin I. Bercea, Daniel Rueckert, Julia Schnabel

What do we learn? Debunking the Myth of Unsupervised Outlier Detection

FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation

Implicit disentanglement of shape and appearance with federated learning for unsupervised brain pathology segmentation.

Cosmin I. Bercea, Benedikt Wiestler, Daniel Rückert, Shadi Albarqouni

FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation

SHAMANN: Shared Memory Augmented Neural Networks

Multiple virtual actors cooperating through shared memory solve medical image segmentation.

Cosmin I. Bercea, Olivier Pauly, Andreas K. Maier, Florin C. Ghesu

SHAMANN: Shared Memory Augmented Neural Networks

Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution

Multi-scale robust super-resolution by jointly optimizing the motion estimation and image reconstruction.

Cosmin I. Bercea, Andreas K. Maier, Thomas Koehler

Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution