A Fast and Adaptive Algorithm to Compute the X-ray Transform

TL;DR

This paper introduces a fast, adaptable algorithm for computing the X-ray transform of images, efficiently handling various geometries and basis functions by analytically determining intersecting units and optimizing calculations.

Contribution

The authors develop a novel, analytic, and adaptable algorithm for X-ray transform computation that improves speed, flexibility, and applicability across multiple scanning geometries.

Findings

Algorithm is faster than existing methods.

Supports multiple geometries including 2D/3D parallel, fan, circular, and helical cone beams.

Demonstrates high accuracy and adaptability through validation experiments.

Abstract

We propose a new algorithm to compute the X-ray transform of an image represented by unit (pixel/voxel) basis functions. The fundamental issue is equivalently calculating the intersection lengths of the ray with associated units. For any given ray, we first derive the sufficient and necessary condition for non-vanishing intersectability. By this condition, we then distinguish the units that produce valid intersections with the ray. Only for those units rather than all the individuals, we calculate the intersection lengths by the obtained analytic formula. The proposed algorithm is adapted to 2D/3D parallel beam and 2D fan beam. Particularly, we derive the transformation formulas and generalize the algorithm to 3D circular and helical cone beams. Moreover, we discuss the intrinsic ambiguities of the problem itself, and present a solution. The algorithm not only possesses the adaptability with regard to the center position, scale and size of the image, but also is suited to parallelize with optimality. The comparison study demonstrates the proposed algorithm is fast, more complete, and is more flexible with respect to different scanning geometries and different basis functions. Finally, we validate the correctness of the algorithm by the aforementioned scanning geometries.