Noise and blur removal from corrupted X-ray computed tomography scans: A multilevel and multiscale deep convolutional framework approach with synthetic training data (BAM SynthCOND)-Reference-Cited by-同舟云学术

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Noise and blur removal from corrupted X-ray computed tomography scans: A multilevel and multiscale deep convolutional framework approach with synthetic training data (BAM SynthCOND)

Published:2023-06 Issue: Volume:2 Page:100011
ISSN:2949-673X
Container-title:Tomography of Materials and Structures
language:en
Short-container-title:Tomography of Materials and Structures

Author:

Tsamos Athanasios^ORCID,Evsevleev Sergei,Bruno Giovanni^ORCID

Publisher

Elsevier BV

Reference36 articles.

1. Adaptive noise reduction toward low-dose computed tomography;Lu;SPIE Proc.,2003

2. Adaptive streak artifact reduction in computed tomography resulting from excessive x-ray photon noise;Hsieh;Med. Phys.,1998

3. Photon starvation artifacts of X-ray CT: their true cause and a solution;Mori;Radiol. Phys. Technol.,2012

4. Stripe and ring artifact removal with combined wavelet - Fourier filtering;Münch;Opt. Express,2009

5. Generalized multi-dimensional adaptive filtering for conventional and spiral single-slice, multi-slice, and cone-beam CT;Kachelrieß;Med. Phys.,2001

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