Wavelet Analysis of Cytological Preparations Image in Different Color Systems - Open Access Library Journal

OALibJ > Vol.4 No.7, July 2017

Open Access Library Journal

Volume 4, Issue 7 (July 2017)

ISSN Print: 2333-9705 ISSN Online: 2333-9721

Google-based Impact Factor: 0.73 Citations

Wavelet Analysis of Cytological Preparations Image in Different Color Systems ()

HTML XML

Download as PDF (Size: 783KB) PP. 1-9

DOI: 10.4236/oalib.1103760 562 Downloads 1,103 Views Citations

Author(s)

Vyacheslav V. Lyashenko¹, Asaad MA. Babker^2*, Valentin A. Lyubchenko¹

Affiliation(s)

¹Department of Informatics, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine.
²Department of Medical Laboratories Science, College of Allied Health Science, Gulf Medical University, Ajman, UAE.

ABSTRACT

Processing of microscope images in medicine is one of the priority research areas. At the same time, the processing of images of cytological preparations occupies a special place. This is due to the fact that such studies allow for a comprehensive diagnosis of the state of human health, identify and prevent the development of diseases in the early stages. But this requires the results of processing the original images, which provide additional information. To do this, we investigate the possibility of using wavelet analysis in color models RGB and HSV. We showed the importance of using the HSV model for more information. It is shown that the procedure for changing the contrast in the HSV model is better than the contrast change procedure in the RGB model when using wavelet analysis.

KEYWORDS

Wavelet Analysis, Image, Contrast Enhancement, Cell, Medicine, Cytology Preparation, Color Systems

Share and Cite:

Lyashenko, V. , Babker, A. and Lyubchenko, V. (2017) Wavelet Analysis of Cytological Preparations Image in Different Color Systems. Open Access Library Journal, 4, 1-9. doi: 10.4236/oalib.1103760.

Cited by

[1]	Image Processing as an Analysis Tool in Medical Research
	2022

[2]	Situational-Linguistic Modeling in Diagnostic Decision-Making Systems
	2022

[3]	Color space image as a factor in the choice of its processing technology
	2021

[4]	Comparative Characteristics of Filtration Methods in the Processing of Medical Images
	2020

[5]	Ключові завдання обробки даних в інтелектуальному аналізі медичних зображень
	2020

[6]	COVID-19 data based on wavelet coherence estimates for selected countries in the Eastern Mediterranean
	2020

[7]	Wavelet Analysis as Research Tool Image Cytological Preparations
	2020

[8]	General Ideology of Analysis Digital Medical Images in RGB Format
	2020

[9]	ИСПОЛЬЗОВАНИЯ БИТОВОГО ПРОЦЕССОРА В ЗАДАЧАХ АНАЛИЗА ИЗОБРАЖЕНИЙ
	2019

[10]	КЛАСИФИКАЦИЯ НА КОМПАКТНЫХ ГИПОТЕЗАХ
	2019

[11]	ДОСЛІДЖЕННЯ ВИБОРУ ПАРАМЕТРІВ НОРМАЛІЗАЦІЇ НАЙПРОСТІШИХ АФІННИХ ПЕРЕТВОРЕНЬ
	2019

[12]	Features of Packaging from Polymers in Pharmaceutics
	2018

[13]	Обнаружение узелков легкого на цифровых медицинских изображениях
	Біоніка інтелекту, 2018

[14]	Виявлення вузлик?в легкого на цифрових медичних зображе
	БИОНИКА ИНТЕЛЛЕКТА, 2018

[15]	Виявлення вузликів легкого на цифрових медичних зображеннях
	2018

[16]	Voice Control for an Industrial Robot as a Combination of Various Robotic Assembly Process Models
	2017

[17]	Software for Voice Control Robot: Example of Implementation
	2017

[18]	Using of Color Model and Contrast Variation in Wavelet Ideology for Study Megaloblastic Anemia Cells
	2017

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journals Menu

Home

About SCIRP

Service

Policies