The color of X-rays: Spectral X-ray computed tomography using energy sensitive pixel detectors

Energy sensitive X-ray imaging detectors are produced by connecting a semiconductor sensor to a spectroscopic pixel readout chip. In this thesis, the applicability of such detectors to X-ray Computed Tomography (CT) is studied.
A prototype Medipix based silicon detector is calibrated using X-ray fluorescence. The charge transport properties of the sensor are characterized using a high energy beam of charged particles at the Super Proton Synchrotron (SPS) at the European Center for Nuclear Research (CERN). Monochromatic X-rays at the European Synchrotron Radiation Facility (ESRF) are used to determined the energy response function. These data are used to implement a physics-based CT projection operator that accounts for the transmission of the source spectrum through the sample and detector effects.
Based on this projection operator, an iterative spectral CT reconstruction algorithm is developed by extending an Ordered Subset Expectation Maximization (OSEM) method. Subsequently, a maximum likelihood based algorithm is implemented by exporting RooFit, an analysis tool widely employed in high energy physics, to CT. Simulations in both cases show that spectral CT is beneficial for minimizing beam hardening artifacts and achieve improved material resolution.
Finally, the results and methods are discussed in terms of their potential societal impact.