Gram filtering and sinogram interpolation for pixel-basis in parallel-beam X-ray CT reconstruction

TL;DR

This paper introduces a method to enhance parallel-beam X-ray CT reconstruction by exact Gram filtering and optimal sinogram interpolation, significantly improving computational efficiency and image quality.

Contribution

It presents a novel approach to compute Gram filters exactly and interpolate sinograms optimally, incorporating detector blur effects efficiently.

Findings

Faster back projection and iterative reconstruction.

Improved image quality on analytical and real CT data.

Effective inclusion of detector blur in the model.

Abstract

The key aspect of parallel-beam X-ray CT is forward and back projection, but its computational burden continues to be an obstacle for applications. We propose a method to improve the performance of related algorithms by calculating the Gram filter exactly and interpolating the sinogram signal optimally. In addition, the detector blur effect can be included in our model efficiently. The improvements in speed and quality for back projection and iterative reconstruction are shown in our experiments on both analytical phantoms and real CT images.