The main goal of my dissertation is to adapt existing image reconstruction techniques for RatCAP in order to counteract errors in the quantitative and qualitative reconstruction results due to its design. RatCAP is a Positron Emission Tomograph with an extremely small Field Of View (FOV) of about 40 mm, and with short scintillation crystals (5 mm). The block detector geometry together, with the small ring diameter, causes significant detector gaps which adversely affects image quality. This unusual and challenging design is required in order to allow the rat to "wear" the tomograph with minimum stress. The initial chapters of this work discuss the predicted performance of RatCAP with deterministic reconstruction methods such as Filtered Back projection (FBP) which is widely used in both human and animal Positron Emission Tomographs (PET) but cannot handle unconventional tomograph geometries. The main part of this work describes the implementation of Monte Carlo Simulations of statistical image reconstruction methods. The accuracy of the reconstructed images will depend on the physical and statistical accuracy of the simulation and the effectiveness of the noise regularization in the reconstruction method.
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