Erratum to: Impact of model-based iterative reconstruction on low-contrast lesion detection and image quality in abdominal CT: a 12-reader-based comparative phantom study with filtered back projection at different tube voltages

Euler, André; Stieltjes, Bram; Szücs-Farkas, Zsolt; Eichenberger, Reto; Reisinger, Clemens; Hirschmann, Anna; Zaehringer, Caroline; Kircher, Achim; Streif, Matthias; Bucher, Sabine; Buergler, David; D’Errico, Luigia; Kopp, Sebastién; Wilhelm, Markus J.; Schindera, Sebastian T.

doi:10.1007/s00330-017-4985-7

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“…16,17 Compared to MBIR, DLR can reconstruct images more quickly and is expected to minimize a change in noise texture that is specific to the iterative reconstruction derived from a low radiation dose or the level of iterative reconstruction. [18][19][20] Therefore, we evaluated DLR in abdominal dynamic CT using U-HRCT. In the present study, we assessed the image noise and spatial resolution characteristics of the DLR algorithm at different radiation doses on abdominal U-HRCT compared with filtered back projection (FBP), hybrid iterative reconstruction (HIR), and MBIR.…”

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confidence: 99%

Image quality improvement with deep learning‐based reconstruction on abdominal ultrahigh‐resolution CT: A phantom study

Shirasaka

Kojima

Funama

et al. 2021

J Applied Clin Med Phys

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In an ultrahigh-resolution CT (U-HRCT), deep learning-based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation doses assuming an abdominal CT protocol.Methods: For the normal-sized abdominal models, a Catphan 600 was scanned by U-HRCT with 100%, 50%, and 25% radiation doses. In all acquisitions, DLR was compared to model-based iterative reconstruction (MBIR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR). For the quantitative assessment, we compared image noise, which was defined as the standard deviation of the CT number, and spatial resolution among all reconstruction algorithms.Results: Deep learning-based reconstruction yielded lower image noise than FBP and HIR at each radiation dose. DLR yielded higher image noise than MBIR at the

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