Impact of an artificial intelligence deep‐learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study-Reference-Cited by-同舟云学术

Impact of an artificial intelligence deep‐learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study

Published:2022-06-24 Issue:8 Volume:49 Page:5052-5063
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Greffier Joël¹,Si‐Mohamed Salim²³,Frandon Julien¹,Loisy Maeliss¹,de Oliveira Fabien¹,Beregi Jean Paul¹,Dabli Djamel¹

Affiliation:

1. IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging Nîmes University Hospital Nîmes France

2. University of Lyon INSA‐Lyon, University Claude Bernard Lyon 1, UJM‐Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206 Villeurbanne France

3. Department of Radiology, Louis Pradel Hospital Hospices Civils de Lyon Bron France

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15807

Reference41 articles.

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2. HsiehJ LiuE NettB TangJ ThibaultJB SahneyS.A new era of image reconstruction: TrueFidelity™. In:Technical White Paper on Deep Learning Image Reconstruction.2019.

3. The evolution of image reconstruction for CT—from filtered back projection to artificial intelligence

4. Deep learning reconstruction of equilibrium phase CT images in obese patients

5. Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

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