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Beam Hardening Correction for Image-Domain Material Decomposition in Photon-Counting CT | IEEE Journals & Magazine | IEEE Xplore

Beam Hardening Correction for Image-Domain Material Decomposition in Photon-Counting CT


Abstract:

Image-domain material decomposition is widely used due to its computational efficiency and compatibility with commonly adopted clinical spectral reconstruction platforms....Show More

Abstract:

Image-domain material decomposition is widely used due to its computational efficiency and compatibility with commonly adopted clinical spectral reconstruction platforms. However, it often suffers from beam hardening artifacts, which can degrade both image quality and diagnostic accuracy. In this study, we propose a beam hardening correction (BHC) method specifically designed for image-domain material decomposition in photon-counting computed tomography (PCCT). Our method utilizes spectral information obtained from the photon-counting detector in PCCT to estimate and correct the beam hardening effect. The measured X-ray spectrum for each energy counter is initially estimated using a sinogram from an off-center water phantom. This spectral information is then applied to compute and correct projection errors induced by beam hardening, thereby enhancing material decomposition accuracy. Extensive qualitative and quantitative evaluations using water and Gammex phantoms (for moderate beam hardening) and a head phantom (for severe beam hardening) validate the effectiveness of the proposed method. Our BHC approach demonstrates significant improvements over existing methods, enabling more accurate and reliable image-domain material decomposition in PCCT applications.
Page(s): 1 - 1
Date of Publication: 10 February 2025

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School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
United Imaging HealthCare, Shanghai, China
United Imaging HealthCare, Shanghai, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
School of Computer Science and Engineering, Southeast University, Nanjing, China
School of Computer Science and Engineering, Southeast University, Nanjing, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China

School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
United Imaging HealthCare, Shanghai, China
United Imaging HealthCare, Shanghai, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
School of Computer Science and Engineering, Southeast University, Nanjing, China
School of Computer Science and Engineering, Southeast University, Nanjing, China
United Imaging HealthCare, Shanghai, China
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China

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