Cosmin i. Bercea

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blue sky with white clouds

Cosmin I. Bercea

Research Scientist

Technical University Munich

Helmholtz Center Munich

In my research, I am dedicated to enhancing medical image analysis by utilizing advanced machine learning and generative artificial intelligence (AI) techniques. Specifically, I am focused on developing improved computer vision methods that enable computers to interpret and comprehend visual information more effectively and integrating these technological advancements into healthcare systems to enhance patient care.

Recently, I have been concentrating on identifying significant patterns within extensive health data sets. This effort is key to more effectively detecting irregularities or 'anomalies', which is vital for early and accurate disease diagnosis during clinical screenings.

Currently, I am pursuing my PhD at the Technical University of Munich (TUM) and Helmholtz Munich, under the guidance of Julia Schnabel and Daniel Rueckert.

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Selected Projects

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Selected Publications

Discover our latest articles

Bercea CI, Wiestler B, Rueckert D, Schnabel JA. Reversing the abnormal: Pseudo-healthy generative networks for anomaly detection.
In: International Conference on Medical Image Computing and Computer-Assisted Intervention, 2023.

Bercea CI, Wiestler B, Rueckert D, Schnabel JA. Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening.
In Medical Imaging with Deep Learning, 2023.

Bercea CI, Wiestler B, Rueckert D, Albarqouni S. Federated disentangled representation learning for unsupervised brain anomaly detection
In Nature Machine Intelligence, 2022.

Teaching

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Software

Experiment with our published code

Automatic Diffusion Models for Unsupervised Anomaly Detection

Pseudo-healthy Generative Networks for Anomaly Detection

Deformable Autoencoders for Unsupervised Anomaly Detection

Towards Universal Anomaly Detection with Generaive AI

Federated Disentangled Brain MRI Pathology Segmentation

Want to connect?

Contact me at cosmin.bercea@tum.de