METHODS FOR DETECTING AND SELECTING AREAS ON TEXTURE BIOMEDICAL IMAGES OF BREAST CANCER

Ainur Orazayeva


L.N. Gumilyov Eurasian National University (Kazakhstan)
http://orcid.org/0000-0002-2899-9886

Jamalbek Tussupov


L.N. Gumilyov Eurasian National University (Kazakhstan)
http://orcid.org/0000-0002-9179-0428

Waldemar Wójcik


Lublin University of Technology (Poland)
http://orcid.org/0000-0002-6473-9627

Sergii Pavlov

psv@vntu.edu.ua
Vinnytsia National Technical University (Ukraine)
http://orcid.org/0000-0002-0051-5560

Gulzira Abdikerimova


L.N. Gumilyov Eurasian National University (Kazakhstan)
http://orcid.org/0000-0002-4953-0737

Liudmyla Savytska


Vinnytsia National Technical University (Ukraine)
http://orcid.org/0000-0003-1130-2621

Abstract

This paper is devoted to topical issues - the development of methods for analyzing texture images of breast cancer. The main problem that is resolved in the article is that the requirements for the results of pre-processing are increasing. As a result of the task, images of magnetic resonance imaging of the breast are considered for image processing using texture image analysis methods. The main goal of the research is the development and implementation of algorithms that allow detecting and isolating a tumor in the breast in women in an image. To solve the problem, textural features, clustering, orthogonal transformations are used. The methods of analysis of texture images of breast cancer, carried out in the article, namely: Hadamard transform, oblique transform, discrete cosine transform, Daubechies transform, Legendre transform, the results of their software implementation on the example of biomedical images of oncological pathologies on the example of breast cancer, it is shown that The most informative for image segmentation is the method based on the Hadamard transform and the method based on the Haar transform. The article presents recommendations for using the results in practice, namely, it is shown that clinically important indicators that make a significant contribution to assessing the degree of pathology and the likelihood of developing diseases, there are other information parameters: diameter, curvature, etc. Therefore, increased requirements for the reliability, accuracy, speed of processing biomedical images.


Keywords:

biomedical image processing, textural features, clustering, orthogonal transformations

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Published
2022-06-30

Cited by

Orazayeva , A. ., Tussupov, J. . ., Wójcik, W. ., Pavlov, S., Abdikerimova, G. ., & Savytska, L. (2022). METHODS FOR DETECTING AND SELECTING AREAS ON TEXTURE BIOMEDICAL IMAGES OF BREAST CANCER. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 12(2), 69–72. https://doi.org/10.35784/iapgos.2951

Authors

Ainur Orazayeva  

L.N. Gumilyov Eurasian National University Kazakhstan
http://orcid.org/0000-0002-2899-9886

Authors

Jamalbek Tussupov 

L.N. Gumilyov Eurasian National University Kazakhstan
http://orcid.org/0000-0002-9179-0428

Authors

Waldemar Wójcik 

Lublin University of Technology Poland
http://orcid.org/0000-0002-6473-9627

Authors

Sergii Pavlov 
psv@vntu.edu.ua
Vinnytsia National Technical University Ukraine
http://orcid.org/0000-0002-0051-5560

Authors

Gulzira Abdikerimova 

L.N. Gumilyov Eurasian National University Kazakhstan
http://orcid.org/0000-0002-4953-0737

Authors

Liudmyla Savytska 

Vinnytsia National Technical University Ukraine
http://orcid.org/0000-0003-1130-2621

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