Thesis: Detection Models for Emission Tomography
Thesis by: -
Advisor:
Tobias Lasser
Supervision by:
Matthias Wieczorek
Abstract
Emission Tomography is a popular clinical tool in the diagnosis of diseases. Based on radioactive tracers marking suspicious targets (such as cancerous cells), emission tomography modalities like Single Photon Emission Computed Tomography (SPECT) or Positron Emission Tomography (PET) allow the non-invasive visualization of these tracers within the human body. Mathematically and algorithmically these modalities pose interesting research problems, in particular the inverse problem of tomographic reconstruction. Central for reconstruction is a suitable physical model of the detection process.
Tasks
The aim of this thesis is the educated selection of a suitable physical detection model for SPECT (potentially also PET) based on established literature, and its efficient implementation in our existing C++ framework for tomographic reconstruction, CAMPRecon. The results should be tested and evaluated both on simulated and real clinical data (in cooperation with our partners at the university clinic MRI).
Requirements
Interest in physical models, C++ programming skills, optionally: GPU programming with OpenCL
Contact