Low-contrast detectability and potential for radiation dose reduction using deep learning image reconstruction—A 20-reader study on a semi-anthropomorphic liver phantom

Low-contrast detectability and potential for radiation dose reduction using deep learning image reconstruction—A 20-reader study on a semi-anthropomorphic liver phantom

Background: A novel deep learning image reconstruction (DLIR) algorithm for CT has recently been clinically approved. Purpose: To assess low-contrast detectability and dose reduction potential for CT images reconstructed with the DLIR algorithm and compare with filtered back projection (FBP) and hyb...

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Bibliographic Details
Main Authors: Tormund Njølstad, Kristin Jensen, Anniken Dybwad, Øyvind Salvesen, Hilde K. Andersen, Anselm Schulz
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:European Journal of Radiology Open
Subjects:
Deep learning image reconstruction
CT
Low-contrast detectability
Online Access:http://www.sciencedirect.com/science/article/pii/S2352047722000259

Internet

http://www.sciencedirect.com/science/article/pii/S2352047722000259

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