Artificial intelligence, in particular from the class of machine learning and deep learning, has shown great promise for application in medical imaging. However, the success of AI-based techniques is limited by the availability and quality of the training data. A common approach is to train methods on well annotated and curated databases of high-quality image acquisitions, which then may fail on real patient cases in a hospital setting. Another problematic is the lack of sufficient numbers of clinical label annotations in the training data, or example for early markers of disease. In this talk I will present some of our recent approaches that aim to address some of these challenges, by using AI as an enabling technique for improved image reconstruction, realistic data augmentation and further downstream tasks. I will conclude by giving an outlook on the future opportunities in this field, operating right from the imaging sensor to extracting clinically relevant measures.
Julia's research interests are in machine/deep learning for image reconstruction, image quality, motion modelling, segmentation and classification tasks in cancer, cardiovascular diseases, and fetal health. In 2021 Julia joined Helmholtz Center Munich (Helmholtz Distinguished Professorship) and Technical University Munich (TUM Liesel Beckmann Distinguished Professorship) as Professor for Computational Imaging and AI in Medicine. She is an Associate Editor and Steering Committee member of IEEE Transactions on Medical Imaging, Associate Editor of IEEE Transactions on Biomedical Engineering, on the Editorial Board of Medical Image Analysis, and Executive Editor of Machine Learning in Biomedical Imaging (melba-journal.org). Julia is a Director of the international Medical Imaging Summer School (MISS), Programme Chair of MICCAI 2018, General Chair of IPMI 2021, and will be General Chair of MICCAI 2024 to be held in Africa for the first time. Julia is Executive Secretary to the MICCAI Society Board of Directors, Technical Representative to the IEEE EMBS Administrative Committee, and was elected Fellow of MICCAI (2018), ELLIS (2019) and IEEE (2021).