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• W2049205912 abstract "Low-dose computed tomography (CT) reduces radiation exposure but decreases signal-to-noise ratio (SNR) and diagnostic capabilities. Noise compensation can improve SNR so low-dose CT can provide valuable information for diagnosis without risking patient radiation exposure. In this study, a novel noise-compensated CT reconstruction method that uses spatially adaptive Monte–Carlo sampling to produce noise-compensated reconstructions is investigated. By adapting to local noise statistics, a non-parametric estimation of the noise-free image is computed that successfully handles non-stationary noise found in low-dose CT images. Using phantom and real low-dose CT images, effective noise suppression is shown to be accomplished while maintaining structures and details." @default.
• W2049205912 created "2016-06-24" @default.
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• W2049205912 date "2013-10-01" @default.
• W2049205912 modified "2023-09-23" @default.
• W2049205912 title "Low-dose computed tomography via spatially adaptive Monte–Carlo reconstruction" @default.
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• W2049205912 doi "https://doi.org/10.1016/j.compmedimag.2013.05.006" @default.
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