Data-driven metal artifact correction in computed tomography using conditional generative adversarial networks-Reference-Cited by-同舟云学术

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Data-driven metal artifact correction in computed tomography using conditional generative adversarial networks

Published:2022-10-18 Issue: Volume: Page:
ISSN:
Container-title:7th International Conference on Image Formation in X-Ray Computed Tomography
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Author:

Blum Nele,Buzug Thorsten M.,Stille Maik

Publisher

SPIE

Reference11 articles.

1. An algorithm for the reduction of metal clip artifacts in CT reconstructions;Glover,1981

2. Development and validation of segmentation and interpolation techniques in sinograms for metal artifact suppression in CT

3. Augmented likelihood image reconstruction with non-local prior image regularization;Stille;Proc. 4th Intl. Mtg. on image formation in X-ray CT,2016

4. Fast Enhanced CT Metal Artifact Reduction using Data Domain Deep Learning;Ghani;IEEE Transactions on Computational Imaging,2019

5. An irregular metal trace inpainting network for x-ray CT metal artifact reduction;Peng,2020

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