Research on CT System Image based on Back Projection Reconstruction Model

CT technology has been widely used in clinical medicine, industrial engineering and other fields in contemporary society. Since the traditional back projection reconstruction algorithm will introduce star artifacts, we decide to use a parallel beam filtered back projection reconstruction model based on Radon changes and R-L filters. Since the rotation center of the system does not coincide with the geometric center, the data will be missing when using Radon transformation, so we carry out "edging" processing on the square tray. After processing the data to remove the gain (where the gain coefficient is 2.0033) and removing the "edge" at the end of the filtering, we reconstructed the detected object and obtained the absorption rates of the ten points required by the problem as follows :0.0126, 2.2902, 5.9159, 0.0163, 0.0823, 3.1336, 6.0333, 0.0000, 7.7184, 0.0861.

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Publication Details

Journal
Frontiers in Computing and Intelligent Systems
Published
2024-11-26
DOI
https://doi.org/10.54097/dmkac495
Primary Topic
Medical Imaging and Analysis
Type
article
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article

Research on CT System Image based on Back Projection Reconstruction Model

Yating Wu, Ruofeng Yu, Ruoyu Yu
Frontiers in Computing and Intelligent Systems
Medical Imaging and Analysis
article

Research on CT System Image based on Back Projection Reconstruction Model

Yating Wu, Ruofeng Yu, Ruoyu Yu
article en

Abstract

CT technology has been widely used in clinical medicine, industrial engineering and other fields in contemporary society. Since the traditional back projection reconstruction algorithm will introduce star artifacts, we decide to use a parallel beam filtered back projection reconstruction model based on Radon changes and R-L filters. Since the rotation center of the system does not coincide with the geometric center, the data will be missing when using Radon transformation, so we carry out "edging" processing on the square tray. After processing the data to remove the gain (where the gain coefficient is 2.0033) and removing the "edge" at the end of the filtering, we reconstructed the detected object and obtained the absorption rates of the ten points required by the problem as follows :0.0126, 2.2902, 5.9159, 0.0163, 0.0823, 3.1336, 6.0333, 0.0000, 7.7184, 0.0861.

Frontiers in Computing and Intelligent SystemsVol. 10(2)
Fujian University of Traditional Chinese Medicine (CN), Xiamen University (CN)
Sustainable cities and communities
Openalex Percentile: Top 80%
Medical Imaging and Analysis
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Research on CT System Image based on Back Projection Reconstruction Model — Yating Wu, Ruofeng Yu, et al. · Frontiers in Computing and Intelligent Systems (2024) | TGRS Research Map | TGRS