A New Statistical Iterative Reconstruction Algorithm for a CT Scanner with Flying Focal Spot

This work is related to the originally formulated 3D statistical model-based iterative reconstruction algorithm adopted to computed tomography with flying focal spot. This new reconstruction method is based on a continuous-to-continuous data model, where the forward model is formulated as a shift invariant system. The proposed approach resembles the well-known Feldkamp (FDK) algorithm, which cannot be used with a flying focal spot scanner as the paths of the X-rays used are not equi-angularly distributed. In this situation, a so-called "nutating" reconstruction algorithm is usually used, which is based on a rebinning methodology, thus transforming the reconstruction problem to that of a parallel beam system. Our approach has some significant advantages compared with the FBP methods. Moreover, although our method belongs to the category of iterative reconstruction approaches, thanks to the fact that our proposed model is derived as a shift invariant system, it is possible to use an FFT algorithm to accelerate the calculations that have to be performed. Because of this, we can obtain diagnostic images in a time comparable to that of FBP methods. Computer simulations have shown that the reconstruction method presented here outperforms referential FBP methods with regard to the image quality obtained and can be competitive in terms of time of calculation.