Paper
3 April 2024 Robust automatic rotation axis alignment mean projection image method in cone-beam and parallel-beam CT
Author Affiliations +
Proceedings Volume 13072, Sixteenth International Conference on Machine Vision (ICMV 2023); 1307212 (2024) https://doi.org/10.1117/12.3023412
Event: Sixteenth International Conference on Machine Vision (ICMV 2023), 2023, Yerevan, Armenia
Abstract
The rotation axis position is an important parameter of classical reconstruction algorithms in X-ray computed tomography (CT). The use of incorrect values of the axis position parameters during the reconstruction leads to the appearance of various artifacts distorting the reconstructed image. Therefore, to obtain a reconstruction of better quality, automatic rotation axis position determination and misalignment correction methods are of use. Most of the existing high-precision automatic rotation axis position determination methods are either fast, but suitable only within a parallel-beam geometric scheme, or indifferent to the geometric scheme, but computationally laborious. In this paper, we propose a method for auto-detection of two scalar parameters of rotation axis position — axis shift and tilt in the plane parallel to the detector window plane — using a pixel-wise arithmetically averaged projection image. The described method is highly accurate within both parallel-beam and cone-beam geometric schemes whereas it is characterized by robustness to noise in projection data. The method has performed an increase in reconstruction quality when compared with some well-known and still used in practice methods both on synthetic data and on real data obtained in real laboratory conditions.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Danil Kazimirov, Anastasia Ingacheva, Alexey Buzmakov, Marina Chukalina, and Dmitry Nikolaev "Robust automatic rotation axis alignment mean projection image method in cone-beam and parallel-beam CT", Proc. SPIE 13072, Sixteenth International Conference on Machine Vision (ICMV 2023), 1307212 (3 April 2024); https://doi.org/10.1117/12.3023412
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
X-ray computed tomography

Automatic alignment

Signal to noise ratio

X-rays

Image restoration

Reconstruction algorithms

CT reconstruction

Back to Top