A scalable neural network architecture for self-supervised tomographic image reconstruction
A scalable neural network architecture for self-supervised tomographic image reconstruction
Authors (15): H. Dong, S. D. M. Jacques, W. Kockelmann, S. W. T. Price, R. Emberson, D. Matras, Y. Odarchenko, V. Middelkoop, A. Giokaris, O. Gutowski, A. ‐C. Dippel, M. von Zimmermann, A. M. Beale, K. T. Butler, A. Vamvakeros
Themes: New Catalysts
DOI: 10.1039/d2dd00105e
Citations: 3
Pub type: journal-article
Pub year: 2023

Publisher: Royal Society of Chemistry (RSC)

Issue:

License: [{"start"=>{"date-parts"=>[[2023, 6, 2]], "date-time"=>"2023-06-02T00:00:00Z", "timestamp"=>1685664000000}, "content-version"=>"vor", "delay-in-days"=>152, "URL"=>"http://creativecommons.org/licenses/by/3.0/"}]

Publication date(s): 2023 (online)

Pages:

Volume: Issue:

Journal: Digital Discovery

Link: [{"URL"=>"http://pubs.rsc.org/en/content/articlepdf/2023/DD/D2DD00105E", "content-type"=>"unspecified", "content-version"=>"vor", "intended-application"=>"similarity-checking"}]

URL: http://dx.doi.org/10.1039/d2dd00105e

We present a lightweight and scalable artificial neural network architecture which is used to reconstruct a tomographic image from a given sinogram.

Name Description Publised
SD2I The Single Digit to Image (SD2I) tensorflow-based image reconstruction t... 2023


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