Search

Monitored tomographic reconstruction (MTR) is a potentially powerful tool for dose and time reduction in computed tomography scanning. We are the first to study the issue of practical implementation of MTR protocols in current-generation real-life instruments. We propose an empirical quantitative model for calculating acquisition and reconstruction times. It is demonstrated that projection acquisition order has a significant impact on the time and dose of tomographic experiments. The new alternative acquisition most suitable for MTR protocols is proposed. To estimate the restrictions and scope of applicability for MTR four typical commercial setups are studied within a proposed model. We construct an experimental stand for achieving a real-time reconstruction, together with validation of the proposed acquisition time model. We demonstrate that real-time reconstruction may be implemented without slowing down an acquisition process. An optimization of reconstruction from partial data is proposed, which allowed the production of 385 and 440 reconstructions for standard and proposed acquisition orders correspondingly during a single acquisition of 512 projections. The results of the study demonstrate that with proposed optimizations MTR can be effectively utilized for practical applications using the current generation of existing setups in industrial and nano tomography fields., Competing Interests: NO authors have competing interests., (Copyright: © 2024 Gilmanov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Ring artifacts pose a major barrier to obtaining precise reconstruction in computed tomography (CT). The presence of ring artifacts complicates the use of automatic means of processing CT reconstruction results, such as segmentation, correction of geometric shapes, alignment of reconstructed volumes. Although there are numerous efficient methods for suppressing ring artifacts, many of them appear to be manual. Along with this, a large proportion of the automatic methods cope unsatisfactorily with the target task while requiring computational capacity. The current work introduces a projection data preprocessing method for suppressing ring artifacts that constitutes a compromise among the outlined aspects - automaticity, high efficiency and computational speed. Derived as the automation of the classical sinogram normalization method, the proposed method specific advantages consist in adaptability in relation to the filtered sinograms and the edge-preservation property proven within the experiments on both synthetic and real CT data. Concerning the challenging open-access data, the method has performed superior quality comparable to that of the advanced methods: it has demonstrated 70.4% ring artifacts suppression percentage (RASP) quality metric. In application to our real laboratory CT data, the proposed method allowed us to gain significant refinement of the reconstruction quality which has not been surpassed by a range of compared manual ring artifacts suppression methods.