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Tissue Germination Evaluation on Implants Based on Shearlet Transform and Color Coding

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Book cover Computer Vision in Advanced Control Systems-5

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 175))

Abstract

The chapter is devoted to computational methods for evaluation the indicators of the tissue regeneration process using as an example the medical data of mesh nickelide titanium implants obtained during clinical experiment. Processing and analysis of scanning electron microscopy and classical histological data are performed using a set of algorithms and their modifications, which allows simplify the data analysis procedure and improve the accuracy of estimates (15–20%). The proposed technique as a computational toolkit for analyzing the dynamics of the process under study, as well as. For highlighting the internal geometric features of the experimental images of objects of interest contains algorithms of shearlet and wavelet transforms and the algorithms for elastic maps generation with color coding, which allows to obtain more representative visualization of spatial data. An important aspect of the proposed methodology is a use of brightness correction by algorithm based on Retinex technology. It allows to obtain unified average brightness of analyzed images and, in some cases, increase local contrast, as a result it affects the quality of application of the computer-based evaluation tools offered in the work. Thus, the estimation errors are reduced by 1–5% in compared to processing without brightness correction.

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Author information

Authors and Affiliations

  1. Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochу pr., 660037, Krasnoyarsk, Russian Federation

    Aleksandr Zotin

  2. Institute of Computational Modelling of the Siberian Branch of the Russian Academy of Sciences, 50/44 Akademgorodok, 660036, Krasnoyarsk, Russian Federation

    Konstantin Simonov

  3. V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 1 Partizana Geleznyaka st., 660022, Krasnoyarsk, Russian Federation

    Fedor Kapsargin & Tatyana Cherepanova

  4. Siberian Federal University, 79 Svobodny pr., 660041, Krasnoyarsk, Russian Federation

    Alexey Kruglyakov

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  1. Aleksandr Zotin
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  2. Konstantin Simonov
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  3. Fedor Kapsargin
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  4. Tatyana Cherepanova
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  5. Alexey Kruglyakov
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Correspondence to Aleksandr Zotin .

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Editors and Affiliations

  1. Department of Informatics and Computer Techniques, Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  2. University of Canberra, Canberra, SA, Australia

    Lakhmi C. Jain

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Zotin, A., Simonov, K., Kapsargin, F., Cherepanova, T., Kruglyakov, A. (2020). Tissue Germination Evaluation on Implants Based on Shearlet Transform and Color Coding. In: Favorskaya, M., Jain, L. (eds) Computer Vision in Advanced Control Systems-5. Intelligent Systems Reference Library, vol 175. Springer, Cham. https://doi.org/10.1007/978-3-030-33795-7_9

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