Paper
10 September 2024 Relationship between contrast-to-noise ratio and ROI concentration and size in X-ray fluorescence computed tomography
Jie Zhong, Jingting Qiu, Renan Xu, Xin Huang, Xiangpeng Li, Shanghai Jiang, Junjie He, Xie Liu
Author Affiliations +
Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 132570S (2024) https://doi.org/10.1117/12.3042722
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China
Abstract
With the advancement of technology and medicine, X-ray CT has been widely used in medical diagnosis, treatment, and monitoring of diseases. This article aims to further optimize the performance of X-ray fluorescence CT system by studying the relationship between contrast-to-noise ratio and the concentration and size of regions of interest (ROI). Using Geant4 XFCT simulation modeling, this study analyzes the impact of ROI concentration and size on the quality of XFCT reconstructed images. To assess the influence of different ROI concentrations on imaging performance of the X-ray fluorescence CT system, the simulation modeling system was adjusted for different ROI sizes, and twenty experimental groups were conducted. The results indicate that ROI concentration and size have a significant impact on imaging quality. Under specific conditions of concentration and size within the region of interest, optimal imaging effects of X-ray fluorescence CT can be achieved. These two factors interact, and when adjusting the parameters of ROI concentration and size to optimize imaging quality, it is necessary to consider the changes in both parameters rather than just the influence of a single parameter.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jie Zhong, Jingting Qiu, Renan Xu, Xin Huang, Xiangpeng Li, Shanghai Jiang, Junjie He, and Xie Liu "Relationship between contrast-to-noise ratio and ROI concentration and size in X-ray fluorescence computed tomography", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 132570S (10 September 2024); https://doi.org/10.1117/12.3042722
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KEYWORDS
X-ray fluorescence spectroscopy

X-ray computed tomography

Monte Carlo methods

Reconstruction algorithms

Image restoration

Expectation maximization algorithms

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