Gram filtering and sinogram interpolation for pixel-basis in parallel-beam X-ray CT reconstruction
This work addresses a computational bottleneck for CT reconstruction applications, but it appears incremental as it builds on existing algorithms with specific optimizations.
The paper tackled the computational burden of forward and back projection in parallel-beam X-ray CT by proposing a method that calculates the Gram filter exactly and interpolates the sinogram signal optimally, resulting in improvements in speed and quality for back projection and iterative reconstruction as shown in experiments on analytical phantoms and real CT images.
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.