Flat-Field Correction of X-Ray Tomographic Images Using Deep Convolutional Neural Networks

It is proposed that neural networks be used to solve the problem of flat-field correction. A process is described for selecting parameters of a deep convolutional neural network in order to solve the problem of flat-field correction with the instability of an empty beam, training this network, and c...

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Bibliographic Details
Published in:Bulletin of the Russian Academy of Sciences. Physics 2023-05, Vol.87 (5), p.604-610
Main Authors: Grigorev, A. Yu, Buzmakov, A. V.
Format: Article
Language:English
Subjects:
Artificial neural networks
Hadrons
Heavy Ions
Nuclear Physics
Physics
Physics and Astronomy
Synchrotrons
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Summary:It is proposed that neural networks be used to solve the problem of flat-field correction. A process is described for selecting parameters of a deep convolutional neural network in order to solve the problem of flat-field correction with the instability of an empty beam, training this network, and checking its operability on the generated data. The procedure is tested on data obtained with laboratory X-ray and synchrotron sources.
ISSN:1062-8738
1934-9432
DOI:10.3103/S1062873822701684