In cancer imaging, advances in MR hardware and software have resulted in the ability to visualize biochemical processes superimposed on anatomic images. For example, the oxygenation status, the acidity, the Brownian motion of water molecules and the blood perfusion can be imaged. Currently, there is a strong interest in determining the value of these functional characteristics as non-invasive biomarkers to evaluate treatment response and outcome. In order to sensitively and reproducibly measure, changes in, these functional parameters, robust and automated processing tools are needed. This research line aims to develop and evaluate image processing techniques for visualization, quantification and integrated analysis of anatomical and functional cancer imaging data.
- Multi-modal image registration: matching MRI with histology
- Multi-modal image analysis of tumour characteristics for treatment monitoring
- Developing tools for hyperthermia treatment planning
- Heterogeneity analysis in DCE-MRI