AI Methods in Radiology

Lead: Dipl.-Ing. Marie-Christine Pali, BSc PhD

Cooperation: Department of Neurology, Department of Neurosurgery, Department of Internal Medicine V, Hematology and Oncology, Department of Machatronics (University of Innsbruck), Priv.-Doz. Dr. Lukas Neumann, Department of Technical Mathematics (University of Innsbruck)

This research group focuses on the development of machine learning and deep learning based methods for the processing and analysis of medical imaging data. The main areas of interest include quantitative image analysis, radiomics, and the development of imaging-derived biomarkers from multimodal imaging data. In addition, the group investigates novel approaches for image representation and feature extraction, including analyses in image and k-space domains, as well as accelerated magnetic resonance imaging (MRI) and generative artificial intelligence (AI). The research group focusses on clinically relevant applications in MRI, computed tomography (CT), dual-energy CT (DECT), photon-counting CT (PCCT), and angiographic imaging. The aim is to develop robust, interpretable and clinically applicable AI-based methods to support improved diagnosis, treatment assessment and clinical decision-making in radiology.