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.uaVinnytsia 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 transformationsReferences
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Authors
Ainur OrazayevaL.N. Gumilyov Eurasian National University Kazakhstan
http://orcid.org/0000-0002-2899-9886
Authors
Jamalbek TussupovL.N. Gumilyov Eurasian National University Kazakhstan
http://orcid.org/0000-0002-9179-0428
Authors
Sergii Pavlovpsv@vntu.edu.ua
Vinnytsia National Technical University Ukraine
http://orcid.org/0000-0002-0051-5560
Authors
Gulzira AbdikerimovaL.N. Gumilyov Eurasian National University Kazakhstan
http://orcid.org/0000-0002-4953-0737
Authors
Liudmyla SavytskaVinnytsia National Technical University Ukraine
http://orcid.org/0000-0003-1130-2621
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