Fast optimal decomposed modification of FDK with potential decreasing of memory consuming

TL;DR

This paper introduces a new 3D cone-beam tomography algorithm that reduces memory usage and accelerates computation, achieving a 20-fold speedup over traditional FDK methods on large images.

Contribution

The paper presents a novel decomposition-based algorithm for 3D cone-beam tomography that significantly decreases memory consumption and increases processing speed compared to existing methods.

Findings

20-fold speedup on large images

Reduced peak memory usage

Comparable or improved reconstruction quality

Abstract

We present a new algorithm for 3D cone-beam tomography. The algorithm is based on decomposition of the cone-beam backprojection operation and angular decimation. It has computational complexity of $O(N^{3.5})$ and allows considerable reduction of peak memory usage in comparison with conventional algorithms. Tests with real data demonstrate the acceleration, achieved by using our algorithm instead of FDK, with 20-fold speedup for a $2000 \times 2000 \times 720$ image. The algorithm is compared with other fast FDK algorithms.