Analysis of color properties of raster images of histological microspecimens: own research experience
DOI:
https://doi.org/10.26641/2307-0404.2022.1.254314Keywords:
analysis, color properties, raster image, microspecimen, computer programAbstract
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
How to Cite
Issue
Section
License
Copyright (c) 2022 Medicni perspektivi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Submitting manuscript to the journal "Medicni perspektivi" the author(s) agree with transferring copyright from the author(s) to publisher (including photos, figures, tables, etc.) editor, reproducing materials of the manuscript in the journal, Internet, translation into other languages, export and import of the issue with the author’s article, spreading without limitation of their period of validity both on the territory of Ukraine and other countries. This and other mutual duties of the author and all co-authors separately and editorial board are secured by written agreement by special form to use the article, the sample of which is presented on the site.
Author signs a written agreement and sends it to Editorial Board simultaneously with submission of the manuscript.