The goal of my research is the development and application of machine learning methods to medical imaging, and their translation into clinical practice so that they can help patients on a day-to-day level. In particular, I am interested in data acquisition and image reconstruction methods that make magnetic resonance imaging faster, more robust against image artifacts, allow imaging of new anatomical or pathological processes, make image interpretation easier and more standardized by moving from qualitative image contrasts to quantitative biomarkers for disease processes, and increase its global availability and accessibility. I serve as the deputy editor of Magnetic Resonance in Medicine for articles from this type of research.
- Accelerated MRI imaging
- Machine Learning for MRI data acquisition and image reconstruction
- Quantitative imaging biomarkers for disease processes
- Increase the global availability of imaging technology in second and third world countries