A Comparison of 4D Cone-Beam CT Algorithms for Slowly Rotating Scanners

The study compares several algorithms for the 4D reconstruction of cone-beam computed tomography (CBCT) data that were recently proposed and which can be used from slowly rotating devices. In our case the imaging units are mounted to linear particle accelerators (LINAC). The algorithms are the conventional phase correlated reconstruction (PC), the McKinnon/Bates-Algorithm, the prior image constrained compressed sensing (PICCS) algorithm, the total-variation minimization (TV) algorithm, and our auto-adaptive phase-correlation (AAPC) algorithm. For each algorithm the same motion-affected rawdata are used and the reconstruction results compared to each other regarding their noise and artifact levels, as well as temporal resolution, and computational complexity and convergence. These criteria result in a discussion of the advantages and disadvantages of each algorithm. The temporal resolution is best in the algorithms which exclusively use data from a single motion phase only. The iterative algorithms show lower noise and artifact levels but are computationally complex and therefore may have a limited usage in the clinical application. Algorithms which include image enhancements beside a faster reconstruction represent a suitable trade-off for the clinical workflow.