Data Science
Research Topics
The aim of our research group is to develop, test and deploy artificial intelligence methods in radiology as well as to perform data curation, pre- and post-processing.
Our current projects include deep learning methods for image segmentation and classification and radiomics feature extraction and selection for image classification. However, with the rapid development of techniques, we are exploring other techniques such as unsupervised methods, generative adversarial networks, combining different sources of data among others.
Research Projects
- Segmentation, Classification and Characterisation of Lymph Nodes
- Classification and Characterisation of Lung Nodules and Masses
- Segmentation, Classification and Characterisation of Brain tumours
- Characterisation of Prostate Lesions
- Radiomics reproducibility
Grants
- RISK – Risk Maps using T2 mapping and Diffusion MR Sequences of the Prostate (ESR Seed Grant Award from the European Society of Radiology (ESR) and the European Institute for Biomedical Imaging Research (EIBIR))
- GAIA – Group for Applied Imaging Application of Artifical Intelligence (Köln Fortune)
MRI research, Radiology department, Uniklinik Köln
Cardiovascular Imaging group, Radiology department, Uniklinik Köln
Machine Learning and Data Science group, Radiology department, Uniklinik Köln
Oncology group, Radiology department, Uniklinik Köln
Stereotaxie Department, Uniklinik Köln
Infection diseases, Internal Medicine, Uniklinik Köln
Cochlear Implant Center, HNO, Uniklinik Köln
Institute of Medical Statistics and Computational Biology, Faculty of Medicine
Center for Data and Simulation Science (CDS), University of Cologne
Multiparametric Imaging and Radiomics - PD Dr. B. Baeßler
Center of Integrated Oncology (CIO)
Philips Research Aachen
Philips Research Hamburg
Jülich Supercomputing Centre
RRZK