My main research focus cover quantification in hybrid imaging, with focus multi-modality imaging systems involving positron emission tomogoraphy (PET). The main focus is on optimization of PET imaging through use of tracer-kinetic modeling, data-driven motion detection and compensation techniques, with main focus on myocardial applications.
Respiratory motion detection in PET imaging systems include external marks such as respiratory belts. These methods needs both planning of which patients might benefit for motion compensation, as well as time to calibrate the systems for the individual patients. After successfull acquisition, the PET data is subdivided into respiratory phases, which increase the noise in the reconstructed PET-images. Data-driven respiratory motion detection and compensation is thus a desired method, where all thoracic PET-acquisitions suited for respiratory can be compensated without planning
Techniques, methods & infrastructure
Mouse models for X-linked adrenoleukodystrophy, ether phospholipid deficiency or Alzheimer’s disease are used for in vivo analysis and primary cells from human patients (e.g. monocytes, lymphoblast or fibroblasts) for in vitro analysis of the role of peroxisomes in proper cellular functioning. A broad spectrum of biochemical, cell biological, and imaging techniques are used.