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Feasibility of thin-slice abdominal CT in overweight patients using a vendor neutral image-based denoising algorithm: Assessment of image noise, contrast, and quality

Akio Tamura, Manabu Nakayama, Yoshitaka Ota, Masayoshi Kamata, Yasuyuki Hirota, Misato Sone, Makoto Hamano, Ryoichi Tanaka and Kunihiro Yoshioka

PLOS ONE, 2019, vol. 14, issue 12, 1-12

Abstract: The purpose of this study was to investigate whether the novel image-based noise reduction software (NRS) improves image quality, and to assess the feasibility of using this software in combination with hybrid iterative reconstruction (IR) in image quality on thin-slice abdominal CT. In this retrospective study, 54 patients who underwent dynamic liver CT between April and July 2017 and had a body mass index higher than 25 kg/m2 were included. Three image sets of each patient were reconstructed as follows: hybrid IR images with 1-mm slice thickness (group A), hybrid IR images with 5-mm slice thickness (group B), and hybrid IR images with 1-mm slice thickness denoised using NRS (group C). The mean image noise and contrast-to-noise ratio relative to the muscle of the aorta and liver were assessed. Subjective image quality was evaluated by two radiologists for sharpness, noise, contrast, and overall quality using 5-point scales. The mean image noise was significantly lower in group C than in group A (p

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0226521

DOI: 10.1371/journal.pone.0226521

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