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“What Do AEs Learn? Challenging Common Assumptions in Unsupervised Anomaly Detection and Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection by Cosmin I. Bercea et al. have been accepted for publication at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2023, which will be held from October 8th to 12th 2023 in Vancouver, Canada.

We are delighted to announce that our research on developing automatic diffusion models for anomaly detection has been accepted and will be published in the proceedings of the 3rd workshop for Interpretable Machine Learning in Healthcare, held at the International Conference on Machine Learning 2023. Congratulations to our dedicated student Michael for his outstanding contribution to this achievement!

“Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening” by Cosmin I. Bercea et al. has been accepted for publication at Medical Imaging with Deep Learning, Nashville, 2023. Cosmin Bercea will present his work on Monday, 10 July 2023 at 9:15 pm CEST.

Veronika Spieker’s and Hannah Eichhorn’s abstracts have been accepted to be presented as digital posters at the 2023 ISMRM & ISMRT Annual Meeting. Veronika Spieker will present her work on “Patient-specific respiratory liver motion analysis for individual motion-resolved reconstruction” on Monday, 05 June 2023 at 1:45 pm EDT.

Federated disentangled representation learning for unsupervised brain anomaly detection by Cosmin I. Bercea et al. has been published at Nature Machine Intelligence.

The MedtecLIVE Talent Award 2022 is given to bachelor’s and master’s theses that relate to an innovation, improvement, or new application in medical technology along with its entire value chain.