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Acceleration of iterative tomographic image reconstruction by reference-based back projection

The purpose of this paper is to design and implement an efficient iterative reconstruction algorithm for computational tomography. We accelerate the reconstruction speed of algebraic reconstruction technique (ART), an iterative reconstruction method, by using the result of filtered backprojection (FBP), a wide used algorithm of analytical reconstruction, to be an initial guess and the reference for the first iteration and each back projection stage respectively. Both two improvements can reduce the error between the forward projection of each iteration and the measurements. We use three methods of quantitative analysis, root-mean-square error (RMSE), peak signal to noise ratio (PSNR), and structural content (SC), to show that our method can reduce the number of iterations by more than half and the quality of the result is better than the original ART.