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

Abdikerimova G. B. et al.: Algorithms and software for the analysis of disordering the structure of cellular walls. Bulletin of the Novosibirsk Computing Center – Series „Сomputer science” 40, 2016, 1–14.
DOI: https://doi.org/10.31144/bncc.cs.2542-1972.2016.n40.p1-14   Google Scholar

Abdikerimova G. B. et al.: Software tools for cell walls segmentation in microphotography. Journal of Theoretical and Applied Information Technology 96, 2018, 4783–4793.
  Google Scholar

Ablyazov T., Baizakov N.: Theory and Practice of Territories Spatial Development Based on the Smart City Concept. In: Rudskoi A., Akaev A., Devezas T. (eds): Digital Transformation and the World Economy. Studies on Entrepreneurship, Structural Change and Industrial Dynamics. Springer, Cham 2022 [http://doi.org/10.1007/978-3-030-89832-8_9].
DOI: https://doi.org/10.1007/978-3-030-89832-8_9   Google Scholar

Arazayeva A. R. et al.: Efficiency of Biomedical Breast Cancer Image Processing Using Filters. The National Academy of Sciences of the Republic of Kazakhstan ¬– Physics and Information Technology Series 1(341), 2022, 69–76 [http://doi.org/10.32014/2022.2518-1726.118].
  Google Scholar

Bayzakov S., Forrest J. Y.-L., Baizakov N. A.: Modeling the management of the economies of developing countries. Advances in Systems Science and Applications 19 (2), 2019, 101–119 [http://doi.org/10.25728/assa.2019.19.2.673].
  Google Scholar

Fu K. S., Mu J. K.: A survey on image segmentation. Pattern Recognition 13(1), 1981, 3–16.
DOI: https://doi.org/10.1016/0031-3203(81)90028-5   Google Scholar

Grady L.: Random walks for image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(11), 2006, 1768–1783.
DOI: https://doi.org/10.1109/TPAMI.2006.233   Google Scholar

Karpinski M., Ziubina R., Azatov A., Shaikhanova A., Teliushchenko V., Falat P.,: Information Security Software Using Quality and Reliability Criteria. IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS), 2020, 1–5 [http://doi.org/10.1109/IDAACS-SWS50031.2020.9297069].
DOI: https://doi.org/10.1109/IDAACS-SWS50031.2020.9297069   Google Scholar

Pavlov S. et al.: System of three-dimensional human face images formation for plastic and reconstructive medicine. In: Arras P., Luengo D. (Eds.): Teaching and subjects on bio-medical engineering Approaches and experiences from the BIOART-project. Acco cv, Leuven 2021, 187–203.
  Google Scholar

Rani R.: Performance analysis of different orthogonal transform for image processing application. International Journal of Applied Research 1(12), 2015, 844–847.
  Google Scholar

Serik M. , Yerlanova G., Karelkhan N. , Temirbekov N.: The Use of the High-Performance Computing in the Learning Process. International Journal of Emerging Technologies in Learning (iJET) 16(17), 2021, 240–254 [http://doi.org/10.3991/ijet.v16i17.22889].
DOI: https://doi.org/10.3991/ijet.v16i17.22889   Google Scholar

Sidorova V. S.: Hierarchical Cluster Algorithm for Remote Sensing Data of Earth. Pattern Recognition and Image Analysis 22(2), 2012, 373–379.
DOI: https://doi.org/10.1134/S1054661812020149   Google Scholar

Stashkevich A. T. et al.: Differential Mueller-matrix tomography of the polycrystalline structure of biological tissues with different damage durations. Proceedings of SPIE 12040, 2021, 120400G.
DOI: https://doi.org/10.1117/12.2617360   Google Scholar

Stashkevich A. T. et al.: Multiparameter polarization-phase microscopy of optically anisotropic networks of biological crystals. Proceedings of SPIE 12040, 2021, 120400F.
DOI: https://doi.org/10.1117/12.2617359   Google Scholar

Stashkevich A. T. et al.: Spectral polarimetry of laser images of biological fluid layers in the differentiation of necrotic conditions. Proceedings of SPIE 12040, 2021, 120400C.
DOI: https://doi.org/10.1117/12.2613344   Google Scholar

Wang J. Z., Du Y.: Scalable integrated region-based image retrieval using IRM and statistical clustering. Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries 2001, 268–277.
DOI: https://doi.org/10.1145/379437.379679   Google Scholar

Wang J. Z., Li J., Wiederhold G.: SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(9), 2001, 947–963.
DOI: https://doi.org/10.1109/34.955109   Google Scholar

Wójcik W., Pavlov S., Kalimoldayev M.:. Information Technology in Medical Diagnostics II. Taylor & Francis Group, CRC Press, Balkema book, London 2019 [http://doi.org/10.1201/ 9780429057618].
DOI: https://doi.org/10.1201/9780429057618   Google Scholar

Wójcik W., Smolarz A. (ed.): Information Technology in Medical Diagnostics. CRC Press 2017.
DOI: https://doi.org/10.1201/9781315098050   Google Scholar

Zhao F., Nagarathnam M.: 5418 Parallel Computer Architecture and Programming Project Report: Implementation and Comparison of Parallel LZ77 and LZ78 Algorithms. 2021.
  Google Scholar

Download


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

Statistics

Abstract views: 235
PDF downloads: 195


Most read articles by the same author(s)

1 2 > >>