Pattern Recognition and Image Analysis

, Volume 28, Issue 4, pp 612–636 | Cite as

Development and Experimental Investigation of Mathematical Methods for Automating the Diagnostics and Analysis of Ophthalmological Images

  • I. B. GurevichEmail author
  • V. V. Yashina
  • S. V. Ablameyko
  • A. M. Nedzved
  • A. M. Ospanov
  • A. T. Tleubaev
  • A. A. Fedorov
  • N. A. Fedoruk
Proceedings of the 6th International Workshop


The paper summarizes the joint work of specialists in the fields of image analysis and ophthalmology over the last few years. As a result of this work, new mathematical methods for automating image analysis that have important diagnostic value for ophthalmology have been developed: (1) identification of the lipid layer state in the intermarginal space of human eyelids; (2) analysis of the degree of cellular structure density (cellularity) in the corneal tissue of human eyes; (3) identification of the state of the retinal blood flow when analyzing fluorescent angiograms of the human fundus; and (4) morphometric analysis of the state of the epithelium posterius (endothelium) in the human eye cornea. As initial data, we used (respectively) (1) images of imprints of the eyelid intermarginal space on a millipore filter upon their osmium vapor staining; (2) micrographs of corneal tissue specimens obtained using a light microscope; (3) fluorescent angiograms of the human fundus; and (4) images of endothelial cells obtained noninvasively using a confocal microscope. The developed methods are designed to extract morphometric data from these images. For each problem, the following results were obtained: (1) expectations and variances of pixel intensities on the imprint along a drawn line and over a selected region, as well as plots that characterize pixel intensity and change in the thickness of the imprint along a drawn line; (2) expectations and variances for the intensities of the selected regions and intensity histograms; (3) extracted vessels and ischemia zones with their statistical descriptions; and (4) detected cells of hexagonal, pentagonal, and other shapes, as well as a set of characteristics associated with the size of the cells detected. The developed methods are based on the fundamental results of the mathematical theory of image analysis and on the joint use of image processing, mathematical morphology, and mathematical statistics techniques. The paper also describes software implementations of the developed methods, including an automated research workstation for ophthalmologists, and presents the results of their experimental testing.


image analysis mathematical morphology automation of scientific research biomedical images ophthalmology intermarginal space of human eyelids angiogram vascular detection extraction of ischemia zones segmentation endothelial layer and epithelium posterius of the eye cornea 


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Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • I. B. Gurevich
    • 1
    Email author
  • V. V. Yashina
    • 1
  • S. V. Ablameyko
    • 2
  • A. M. Nedzved
    • 2
    • 3
  • A. M. Ospanov
    • 4
  • A. T. Tleubaev
    • 4
  • A. A. Fedorov
    • 5
  • N. A. Fedoruk
    • 5
  1. 1.Federal Research Center “Computer Sciences and Control” of the Russian Academy of SciencesMoscowRussia
  2. 2.Belarusian State UniversityMinskBelarus
  3. 3.United Institute of Informatics Problems of the National Academy of Sciences of BelarusMinskBelarus
  4. 4.Faculty of Computational Mathematics and CyberneticsMoscow State UniversityMoscowRussia
  5. 5.Scientific Research Institute of Eye DiseasesMoscowRussia

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