oking stained images preserving the inter-cellular structures, crucial for the medical experts to perform classification. We achieve better structure preservation by adding …
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 …
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 …
This 5 years Helmholtz funded project to advance the field with Federated Learning algorithms in Medicine (2020-2025)
DAAD Funded Project with ETH Zürich and Imperial College London (2020-2022)
Abstract Purpose: To evaluate the benefit of the additional available information present in spectral CT datasets, as compared to conventional CT …
Chest X-ray radiography is one of the earliest medical imaging technologies and remains one of the most widely-used for diagnosis, screening, and treatment follow up of diseases …
Generative adversarial networks (GANs) and their extensions have carved open many exciting ways to tackle well known and challenging medical image analysis problems such as medical …
European IMI2 consortium building the largest platform of digital pathology images for AI (2021–2027). We took part at TU Munich, contributing federated learning, until 2020.
Dual Energy CT is a modern imaging technique that is utilized in clinical practice to acquire spectral information for various diagnostic purposes including the identification, …