Non-Positive Corrections and Variance Models for Iterative Post-Log Reconstruction of Extremely Low-Dose CT Data
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Title
- Non-Positive Corrections and Variance Models for Iterative Post-Log Reconstruction of Extremely Low-Dose CT Data
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Alternative Title
- Non-Positive Corrections and Variance Models for Iterative Post-Log Reconstruction of Extremely Low-Dose CT Data
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Author(s)
- Kim Soo Mee; Lee Tzu-Cheng; Kinahan Paul E.
- KIOST Author(s)
- Kim, Soo Mee(김수미)
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Alternative Author(s)
- 김수미
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Publication Year
- 2020-07
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Abstract
- In extremely low-dose protocols to reduce radiation dose to patients, computed tomography (CT) images suffer from increased bias and low signal-to-noise ratio in measurements. In this study, we consider three different non-positive corrections, flip, truncation and mean-preserving filter (MPF), affecting the measurement mean, propose a new variance expression for weights in weighted least-squares (WLS) reconstruction, and evaluate the impact on changes in the mean and variance of measurements. We simulated 1000 polychromatic CT sinograms of a chest phantom, including realistic levels of quantum and electronic noises. For the simulated scenario of 80 kVp and 0.5 mAs, compared to the conventional threshold and flip methods, the mean-preserving filter reduced the bias in post-log sinogram values by up to five times. Simple weights in WLS reconstruction that neglected the effect of non-positive correction limited improvements in the image quality. The advanced variance estimates considering electronic noise and the effect of pre-processing on the variance change made both WLS and penalized WLS reconstructions improve. Although the image quality improvement from a WLS reconstruction based on a Gaussian post-log distribution is inherently limited, the proposed method for estimating the post-log variance including electronic noise and the effect of pre-corrections from a single measurement leads to some improvements in variance estimates for post-log CT data and showed the feasibility of post-log iterative reconstruction for extremely low-dose CT imaging.
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ISSN
- 0374-4884
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/38600
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DOI
- 10.3938/jkps.77.177
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Bibliographic Citation
- JOURNAL OF THE KOREAN PHYSICAL SOCIETY, v.77, no.2, pp.177 - 185, 2020
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Publisher
- KOREAN PHYSICAL SOC
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Subject
- IMAGE QUALITY; ABDOMINAL CT; REDUCTION; PATIENT
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Keywords
- CT iterative reconstruction; Low-dose CT imaging; Statistical post-log CT model
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Type
- Article
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Language
- English
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Document Type
- Article
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