What is it about?
The article briefly reviews reconstruction algorithms for few-view computed tomography, which have been developed by the authors in the last 15 years. The development trend of the applied approaches is traced: from a simple modification of algebraic reconstruction to deep learning methods.
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Why is it important?
In the opinion of the authors, of particular interest is tracing the фдпщкшерь development trend: modifications of traditional algebraic reconstruction - compressed sensing algorithms - hybrid algorithms using deep learning methods.
Perspectives
The authors' research in the field of developing new algorithms for few-view computed tomography continues. And there is hope that in 5-7 years the authors will present a new review on this topic.
Dr. Alexander B Konovalov
Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All-Russia Research Institute of Technical Physics,” Snezhinsk, Russia
Read the Original
This page is a summary of: Development of Image Reconstruction Algorithms for Few-View Computed Tomography at RFNC–VNIITF: History, State of the Art, and Prospects, Russian Journal of Nondestructive Testing, June 2022, Pleiades Publishing Ltd,
DOI: 10.1134/s1061830922060067.
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