This paper presents some practical realizations of image reconstruction methods for spiral cone-beam tomography scanners in which an X-ray tube with a flying focal spot is used. These methods are related to the original formulated 3D statistical model-based iterative reconstruction approach for tomography with flying focal spot. The conception proposed here is based on principles of a statistical model-based iterative reconstruction (MBIR) methodology, where the reconstruction problem is formulated as a shift-invariant system (a continuous-to-continuous data model). We adopted nutating reconstruction-based approaches, i.e. the advanced single slice rebinning methodology (usually applied in CT scanners with X-ray tubes with a flying focal spot), and a procedure compliant with the FDK scheme. We showed that our methods significantly improve the quality of obtained images compared to the traditional FBP algorithms. Consequently, it can allow for a reduction in the x-ray dose absorbed by a patient. Additionally, we show that our approach can be competitive in terms of the time of calculations, especially if we consider commercially used statistical reconstruction systems.
The presented here abstract presents shortly an iterative approach to reconstruction problem for positron emission tomography (PET) imaging technique. The conception proposed here is based on a continuous-to-continuous data model, and a reconstruction problem is formulated as a shift-invariant system. The reconstruction problem is formulated taking into consideration the statistical properties of signals obtained by PET scanner. Computer simulations have been performed which prove that the reconstruction algorithm described here significantly overperforms EM-ML method based on discrete-to discrete data model on the quality of the images obtained.
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