A robust geometry estimation method for spiral, sequential and circular cone‐beam micro‐CT

Purpose: The authors propose a novel method for misalignment estimation of micro‐CT scanners using an adaptive genetic algorithm. Methods: The proposed algorithm is able to estimate the rotational geometry, the direction vector of table movement and the displacement between different imaging threads of a dual source or even multisource scanner. The calibration procedure does not rely on dedicated calibration phantoms and a sequence scan of a single metal bead is sufficient to geometrically calibrate the whole imaging system for spiral, sequential, and circular scan protocols. Dual source spiral and sequential scan protocols in micro‐computed tomography result in projection data that—besides the source and detector positions and orientations—also require a precise knowledge of the table direction vector to be reconstructed properly. If those geometric parameters are not known accurately severe artifacts and a loss in spatial resolution appear in the reconstructed images as long as no geometry calibration is performed. The table direction vector is further required to ensure that consecutive volumes of a sequence scan can be stitched together and to allow the reconstruction of spiral data at all. Results: The algorithm's performance is evaluated using simulations of a micro‐CT system with known geometry and misalignment. To assess the quality of the algorithm in a real world scenario the calibration of a micro‐CT scanner is performed and several reconstructions with and without geometry estimation are presented. Conclusions: The results indicate that the algorithm successfully estimates all geometry parameters, misalignment artifacts in the reconstructed volumes vanish, and the spatial resolution is increased as can be shown by the evaluation of modulation transfer function measurements.