Approximating algebraic tomography methods by filtered backprojection: a local filter approach

Filtered Backprojection is the most widely used reconstruction method in transmission tomography. The algorithm is computationally efficient, but requires a large number of low-noise projections acquired over the full angular range to produce accurate reconstructions. Algebraic reconstruction methods on the other hand are in general more robust with respect to noise and can incorporate the available angular range in the underlying projection model. A drawback of these methods is their higher computational cost. In a recent article, we demonstrated that for \emph{linear algebraic reconstruction methods}, a filter can be computed such that applying Filtered Backprojection using this filter yields reconstructions that approximate the algebraic method. In the present work, we explore a modification of this approach, where we use more than one algebraic filter in the reconstructions, each covering a different region of the reconstruction grid. We report the results of a series of experiments to determine the how well the reconstruction and approximation accuracy of this approach.