Using deep learning-based denoising and iterative reconstruction to reduce radiation exposure – How low can we go?-Reference-Cited by-同舟云学术

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Using deep learning-based denoising and iterative reconstruction to reduce radiation exposure – How low can we go?

Published:2024-04 Issue: Volume:173 Page:111376
ISSN:0720-048X
Container-title:European Journal of Radiology
language:en
Short-container-title:European Journal of Radiology

Author:

Schindler Philipp,Gerwing Mirjam^ORCID

Publisher

Elsevier BV

Reference6 articles.

1. Radiation exposure from pediatric CT scans and subsequent cancer risk in the netherlands;Meulepas;J Natl Cancer Inst.,2019

2. Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction;Klemenz;Sci Rep.,2024

3. Deep learning-based reconstruction improves the image quality of low-dose CT colonography;Chen;Acad. Radiol..,2024

4. Deep learning image reconstruction for CT: technical principles and clinical prospects;Koetzier;Radiology.,2023

5. Deep-learning CT reconstruction in clinical scans of the abdomen: a systematic review and meta-analysis;Shehata;Abdom Radiol (NY).,2023

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