Open Medical Inference (OMI)
BMBF Funded Project through Medical Informatics Initaitive (MII) consortia (2024-2028)
Joint self-supervised image-volume representation learning with intra-inter contrastive clustering
Collecting large-scale medical datasets with fully annotated samples for training of deep networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs …
Deep learning to estimate aging from chest imaging
The 3-year DFG Funded project with UniKlinikum Freiburg (2023-2026)
Federated disentangled representation learning for unsupervised brain anomaly detection
Recent advances in Deep Learning (DL) and the increased use of brain MRI have provided a great opportunity and interest in automated anomaly segmentation to support human …
What can we learn about a generated image corrupting its latent representation?
Generative adversarial networks (GANs) offer an effective solution to the image-to-image translation problem, thereby allowing for new possibilities in medical imaging. They can …
Flamby: Datasets and benchmarks for cross-silo federated learning in realistic healthcare settings
Federated Learning (FL) is a novel approach enabling several clients holding sensitive data to collaboratively train machine learning models, without centralizing data. The …
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Development of a Deep Learning Toolkit for MRI-Guided Online Adaptive Radiotherapy
The 3-year DFG Funded project with the University Hospital Bonn, LMU and TU Munich (2022-2025)
Multi-task multi-domain learning for digital staining and classification of leukocytes
oking stained images preserving the inter-cellular structures, crucial for the medical experts to perform classification. We achieve better structure preservation by adding …
An Uncertainty-Driven GCN Refinement Strategy for Organ Segmentation
Organ segmentation in CT volumes is an important pre-processing step in many computer assisted intervention and diagnosis methods. In recent years, convolutional neural networks …
Uncertainty-based graph convolutional networks for organ segmentation refinement
Organ segmentation is an important pre-processing step in many computer assisted intervention and diagnosis methods. In recent years, CNNs have dominated the state of the art in …