A deep learning reconstruction framework for X-ray computed tomography with incomplete data

As a powerful imaging tool, X-ray computed tomography (CT) allows us to investigate the inner structures of specimens in a quantitative and nondestructive way. Limited by the implementation conditions, CT with incomplete projections happens quite often. Conventional reconstruction algorithms are not...

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Detalles Bibliográficos
Autores principales: Dong, Jianbing, Fu, Jian, He, Zhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6824569/
https://www.ncbi.nlm.nih.gov/pubmed/31675363
http://dx.doi.org/10.1371/journal.pone.0224426

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6824569/
https://www.ncbi.nlm.nih.gov/pubmed/31675363
http://dx.doi.org/10.1371/journal.pone.0224426

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