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New Method for Automating the Diagnostic Analysis of Human Fundus Images Produced by Optical Coherent Tomography Angiography. Research and Software Kit Realization

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Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges (ICPR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13644))

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Abstract

This article presents the results of the joint work of specialists in the field of image analysis and ophthalmologists on the task of analyzing images obtained by the method of optical coherence tomography angiography. A descriptive algorithmic scheme for analyzing images obtained using optical coherence tomography angiography is built to automate the detection of pathological changes in the morphometric characteristics of the fundus. The algorithmic scheme is based on the methods of image processing, analysis, and recognition. The previously developed feature space is supplemented and modified, based on which it is possible to identify pathological changes in the structure of the choroid plexuses of the human retina. It was possible to improve the accuracy of classifying images of healthy and pathological eyes, as well as significantly increasing the accuracy of classification of borderline cases. Software is created that makes it possible to accurately carry out differential diagnostics of the normal state of vessels from the pathological one in the offline mode, which increases its diagnostic value. It is planned to achieve higher classification accuracy results for all three cases.

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Authors and Affiliations

  1. Federal Research Center “Computer Science and Control” Russian Academy of Sciences, Building 2, 44, Vavilov street, Moscow, 119333, Russian Federation

    I. B. Gurevich, V. V. Yashina & A. T. Tleubaev

Authors
  1. I. B. Gurevich
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  2. V. V. Yashina
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  3. A. T. Tleubaev
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Corresponding author

Correspondence to V. V. Yashina .

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Editors and Affiliations

  1. York University, Toronto, ON, Canada

    Jean-Jacques Rousseau

  2. Ontario Tech University, Oshawa, ON, Canada

    Bill Kapralos

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Gurevich, I.B., Yashina, V.V., Tleubaev, A.T. (2023). New Method for Automating the Diagnostic Analysis of Human Fundus Images Produced by Optical Coherent Tomography Angiography. Research and Software Kit Realization. In: Rousseau, JJ., Kapralos, B. (eds) Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. ICPR 2022. Lecture Notes in Computer Science, vol 13644. Springer, Cham. https://doi.org/10.1007/978-3-031-37742-6_36

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  • DOI: https://doi.org/10.1007/978-3-031-37742-6_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37741-9

  • Online ISBN: 978-3-031-37742-6

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