Abstract:
The method of computer tomography is used for studying the internal structure of an object without its physical destruction. If the object contains highly absorbing inclusions, the reconstructed image contains characteristic artifacts called "metal". Such distortions may conceal or simulate both pathologies in medical research and, for example, stress states or cracks in products in the case of industrial use of the method. The paper analyzes possible sources of artifacts. The results of the reconstruction of a baby tooth image measured on a laboratory microtomograph are discussed. The tooth was removed before the end of the root resorption process, which made it possible to strengthen the strongly absorbing particle in thecavity between the roots before the measurements. The presence of a strongly absorbing inclusion gave rise to artifacts in the reconstructed image. This work is devoted to the analysis of the possibility of reducing these artifacts. In addition to visual comparison of the results of reconstruction of the tooth cross-section without inclusion and the results of reconstruction in the presence of inclusion calculated values of metrics RMSE and SSIM. The obtained results show that application of algebraic approach allows improving the reconstruction quality in the presence of strongly absorbing inclusions.
Citation:
M. V. Chukalina, A. V. Buzmakov, A. S. Ingacheva, Ya. L. Shabelnikova, V. E. Asadchikov, I. N. Bukreeva, D. P. Nikolaev, “Analysis of the tomographic reconstruction from polychromatic projections for objects with highly absorbing inclusions”, Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2020, no. 3, 49–61
\Bibitem{ChuBuzIng20}
\by M.~V.~Chukalina, A.~V.~Buzmakov, A.~S.~Ingacheva, Ya.~L.~Shabelnikova, V.~E.~Asadchikov, I.~N.~Bukreeva, D.~P.~Nikolaev
\paper Analysis of the tomographic reconstruction from polychromatic projections for objects with highly absorbing inclusions
\jour Informatsionnye Tekhnologii i Vychslitel'nye Sistemy
\yr 2020
\issue 3
\pages 49--61
\mathnet{http://mi.mathnet.ru/itvs418}
\crossref{https://doi.org/10.14357/20718632200305}
Linking options:
https://www.mathnet.ru/eng/itvs418
https://www.mathnet.ru/eng/itvs/y2020/i3/p49
This publication is cited in the following 1 articles:
A. S. Ingacheva, M. I. Gilmanov, A. V. Yamaev, A. V. Buzmakov, D. D. Kazimirov, I. A. Kunina, Zh. V. Soldatova, M. V. Chukalina, V. V. Arlazarov, “Computer Tomography as an Artificial Intelligence Instrument—the Survey of Approach and Results of V.L. Arlazarov's Scientific School”, Pattern Recognit. Image Anal., 33:4 (2023), 769
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