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Image Quality Assessment of Low-Dose CT using Hybrid Iterative Reconstruction

机译:Image Quality Assessment of Low-Dose CT using Hybrid Iterative Reconstruction

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摘要

Background: X-ray computed tomography is the first imaging technology that supports accurate nondestructive interior image reconstruction of an object from sufficient projection data. Low-dose computed tomography (LDCT) has been considered to relieve the harm to patients caused by X-ray radiation. However, LDCT images can be degraded by quantum noise and streak artifacts. Methods: The objective of the authors' study is to evaluate the optimal level of the hybrid iterative reconstruction (HIR) that generates images with the best diagnostic quality on different dose and noise levels. HIR with optimizations is proposed to reduce image noise and provide better performance at a low dose. The Catphan (R) 504 phantom is employed to assess various image qualities (IQ). Results: For any given scanning protocols, there is linear noise reduction and linear increase of contrast-to-noise ratio (CNR) using optimal HIR. The evidence from various module tests demonstrates that the shape of the noise power spectrum is continuously shifted to low frequency with increasing HIR levels compared with that of filtered-back-projection (FBP). This may describe the difference between the human observer performance and features of the ideal low-contrast objects. Conclusion: Optimal HIR is clearly demonstrated to be a superior method for reducing image noise and improving CNR compared to FBP. Optimal HIR also inhibits texture change or spectrum shift compared with the pure IR method. Even though there are continuous noise reduction and CNR increase with HIR at increasing levels, the human observer performance does not seem to improve simultaneously due to coarser noise (low-frequency noise). HIR level 3 to 5 is optimal for their study. It is possible for the optimal HIR to offer equivalent diagnostic IQ at a lower dose compared with FBP at a routine dose. (C) 2021 Society for Imaging Science and Technology.

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  • 来源
    《Journal of Imaging Science and Technology》 |2021年第6期|60501.1-60501.11|共11页
  • 作者单位

    Beijing Hosp, Beijing 100730, Peoples R China|Natl Ctr Gerontol, Beijing 100730, Peoples R China|Chinese Acad Med Sci, Inst Geriatr Med, Beijing 100730, Peoples R China;

    Hangzhou Dianzi Univ, Coll Comp Sci, Hangzhou 310018, Zhejiang, Peoples R China|Minist Ind & Informat Technol China, Key Lab Intelligent Image Anal Sensory & Cognit H, Hangzhou 310018, Zhejiang, Peoples R China;

    Hangzhou Dianzi Univ, Coll Comp Sci, Hangzhou 310018, Zhejiang, Peoples R China|Nankai Univ, Coll Life Sci, Tianjin 300071, Peoples R China;

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  • 正文语种 英语
  • 中图分类 摄影技术;
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