A New Statistical Reconstruction Method for the Computed Tomography Using an X-Ray Tube with Flying Focal Spot

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Artificial Intelligence and Soft Computing Research Pub Date : 2021-10-01 DOI:10.2478/jaiscr-2021-0016
R. Cierniak, P. Pluta, M. Waligóra, Z. Szymanski, K. Grzanek, Filip Pałka, V. Piuri
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引用次数: 1

Abstract

Abstract This paper presents a new image reconstruction method for spiral cone- beam tomography scanners in which an X-ray tube with a flying focal spot is used. The method is based on principles related to the statistical model-based iterative reconstruction (MBIR) methodology. The proposed approach is a continuous-to-continuous data model approach, and the forward model is formulated as a shift-invariant system. This allows for avoiding a nutating reconstruction-based approach, e.g. the advanced single slice rebinning methodology (ASSR) that is usually applied in computed tomography (CT) scanners with X-ray tubes with a flying focal spot. In turn, the proposed approach allows for significantly accelerating the reconstruction processing and, generally, for greatly simplifying the entire reconstruction procedure. Additionally, it improves the quality of the reconstructed images in comparison to the traditional algorithms, as confirmed by extensive simulations. It is worth noting that the main purpose of introducing statistical reconstruction methods to medical CT scanners is the reduction of the impact of measurement noise on the quality of tomography images and, consequently, the dose reduction of X-ray radiation absorbed by a patient. A series of computer simulations followed by doctor’s assessments have been performed, which indicate how great a reduction of the absorbed dose can be achieved using the reconstruction approach presented here.
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一种新的x射线管飞焦点ct统计重建方法
摘要本文提出了一种新的螺旋锥束断层扫描仪图像重建方法,该方法采用带飞行焦斑的x射线管。该方法基于基于统计模型的迭代重建(MBIR)方法的相关原理。提出的方法是一种连续到连续的数据模型方法,并将前向模型表述为移位不变系统。这可以避免基于章动重建的方法,例如,通常应用于带有飞行焦斑的x射线管的计算机断层扫描(CT)扫描仪的高级单片重建方法(ASSR)。反过来,所建议的方法可以大大加快重建处理,并且通常大大简化整个重建程序。此外,与传统算法相比,它提高了重建图像的质量,大量的仿真结果证实了这一点。值得注意的是,将统计重建方法引入医用CT扫描仪的主要目的是减少测量噪声对断层扫描图像质量的影响,从而减少患者吸收的x射线辐射剂量。在医生的评估之后进行了一系列的计算机模拟,这表明使用这里提出的重建方法可以实现吸收剂量的减少。
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来源期刊
Journal of Artificial Intelligence and Soft Computing Research
Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
7.00
自引率
25.00%
发文量
10
审稿时长
24 weeks
期刊介绍: Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.
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