Analysis of color properties of raster images of histological microspecimens: own research experience

Authors

DOI:

https://doi.org/10.26641/2307-0404.2022.1.254314

Keywords:

analysis, color properties, raster image, microspecimen, computer program

Abstract

This study is aimed to develop a computer program to analyze the color properties of raster images of histological microspecimens used in pathological anatomy and forensic medicine. When developing a computer program, we used the system for building client applications – Windows Presentation Foundation (WPF). The system allows you to create applications with visually attractive user interaction capabilities. The programming language is C#, as well as basic graphics capabilities of the .NET Framework system are used. To speed up the display we applied double buffering. In the course of the research, the authors developed a modern computer program «Analysis of color properties of raster images». This program allows you to analyze the color of each individual pixel of a photograph in RGB and Lab color models, comparing the colors and brightness of individual pixels, selecting groups of points and determining statistical characteristics of them. Characteristic points are well distinguishable in the photographs, studied with the program «Analysis of color properties of raster images». This makes it possible to select and automate these properties, using computer recognition algorithms, completely removing human factor’s influence on the analysis results. The computer program «Analysis of color properties of raster images» is of significant scientific and practical interest for specialists both in the field of morphology (pathologists, forensic experts, etc.), and in the field of other biomedical disciplines.

References

Volkov V. [To the assessment of indicators in morphological medicobiological researches: correction of approach to new complex statistical algorithm]. Bulletin of science and practice. 2016;6:75-84. Russian.

Gorbunova EV, Chertov AN. [Colorimetry of radiation sources: textbook]. SPb: Universitet ITMO; 2015. p. 126. Russian.

Erofeev SV, Shishkin YY, Fedorova AS. [About the technology of image analysis as a means of increasing the objectivity and reliability of forensic examinations]. Russian Journal of Forensic Medicine. 2017;3(2):17-23. Russian.

doi: https://doi.org/10.19048/2411-8729-2017-3-2-17-23

Kitrar LA, Lipkind TM, Ostapkovich GV. [Quantification of qualitative variables in business surveys]. Voprosy statistiki. 2018;25(4):49-63. Russian.

Kovalskiy BМ, Dudiak VО, Zanko NV, Pysanchyn NS. [Interaction of basic concepts of colour theory with colour perpoduction in modern digital systems]. Printing and publishing. 2018;1(75):19-30. Ukrainian. doi: https://doi.org/10.32403/0554-4866-2018-1-75-19-30

Review Bagriy MM, Dibrova VA, Popadynets OG, Grischuk MI. [Methods of morphological research]. Bagriy MM, Dibrova VA, editors. Vinnitsa: New book; 2016. p. 328. Ukrainian.

Myroshnychenko MS, Dyadyk OO, Olkhovsky VO, Grygorian EK. [Digital technologies and their diagnostic value in pathological anatomy and forensic medicine: current state of the problem]. Collection of scientific article of the 3 International scientific and practical conference «Informational systems and technologies in medicine» (November 26-27, 2020, Kharkiv). Kharkiv: HNURE; 2019. p. 59-60. Ukrainian.

Poslavska OV. [Methodology for the use of software for the analysis of digital micrographs on the base of pathomorphology course in order to increase the profes¬sional level of students and scientists]. Morphologia. 2015;9(3):122-6. Ukrainian. doi: https://doi.org/10.26641/1997-9665.2015.3.122-126

Starovoitov VV, Golub YuI. [Digital images: from acquisition to processing]. Minsk: OIPI NAN Belarusi; 2014. p. 202. Russian.

Dhingra V, Juglan S. Importance of medico legal expert at scene of crime related to death. Journal of forensic sciences and criminal investigation. 2017;6(1). doi: https://doi.org/10.19080/JFSCI.2017.06.555682

Gurcan MN, Boucheron LE, Can A, Madabhushi A, Rajpoot NM, Yener B. Histopathological image analysis: a review. IEEE Rev Biomed Eng. 2009;2:147-71. doi: https://doi.org/10.1109/RBME.2009.20348655.

Schindelin J, Rueden CT, Hiner MC, Eliceiri KW. The ImageJ ecosystem: an open platform for biomedical image analysis. Mol Reprod Dev. 2015;1-12.

Silva LFF, Saldiva PHN, Alves VAF. History and prospects of pathology in medicine. Revista de Medicina. 2016;95(2):68-72.

doi: https://doi.org/10.11606/issn.1679-9836.v95ispe2p68-72

Windows Presentation Foundation. [Internet]. Available from: https://ru.wikipedia.org/wiki/Windows_Presentation_Foundation

Downloads

Published

2022-03-30

How to Cite

1.
Ivanova M, Myroshnychenko M, Khara G, Arseniev O, Olkhovsky V, Grygorian E, Fedulenkova Y, Kozlov S. Analysis of color properties of raster images of histological microspecimens: own research experience. Med. perspekt. [Internet]. 2022Mar.30 [cited 2024Apr.25];27(1):9-15. Available from: https://journals.uran.ua/index.php/2307-0404/article/view/254314

Issue

Section

THEORETICAL MEDICINE