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- W2947682034 abstract "The iterative reconstruction methods ASiR and ASiR-V have been accepted by hundreds of sites as their standard of care for a variety of protocols and applications. While the reduction in noise has been significant some readers have a preference for the classic image appearance. To maintain the classic image appearance of FBP at the same dose levels used for the standard of care with ASiR-V we introduce, Deep Learning Image Reconstruction (DLIR), a technique using artificial neural networks. This paper demonstrates that DLIR can maintain or improve upon the performance of the conventional iterative reconstruction algorithm (ASiR-V) in terms of low contrast detectability, noise, and spatial resolution." @default.
- W2947682034 created "2019-06-07" @default.
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- W2947682034 date "2019-05-28" @default.
- W2947682034 modified "2023-09-26" @default.
- W2947682034 title "Evaluation of image quality of a deep learning image reconstruction algorithm" @default.
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- W2947682034 doi "https://doi.org/10.1117/12.2534961" @default.
- W2947682034 hasPublicationYear "2019" @default.
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