150 citations · 181 across the 4 of their papers we have counts for
5 papers
Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Data
Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz +2
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper eval…
Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging
Ilyas Sirazitdinov, Heinrich Schulz, Axel Saalbach +2
Chest X-ray is one of the most widespread examinations of the human body. In interventional radiology, its use is frequently associated with the need to visualize various tube-like…
Anomaly Detection in Medical Imaging with Deep Perceptual Autoencoders
Nina Shvetsova, Bart Bakker, Irina Fedulova +2
Anomaly detection is the problem of recognizing abnormal inputs based on the seen examples of normal data. Despite recent advances of deep learning in recognizing image anomalies,…
Continual Learning for Domain Adaptation in Chest X-ray Classification
Matthias Lenga, Heinrich Schulz, Axel Saalbach
Over the last years, Deep Learning has been successfully applied to a broad range of medical applications. Especially in the context of chest X-ray classification, results have bee…
Synthetic CT Generation from MRI Using Improved DualGAN
Denis Prokopenko, Joël Valentin Stadelmann, Heinrich Schulz +2
Synthetic CT image generation from MRI scan is necessary to create radiotherapy plans without the need of co-registered MRI and CT scans. The chosen baseline adversarial model with…