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Detection of lung pathology using the fractal method

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 6 (2023)

DOI
10.11591/ijece.v13i6.pp6778-6786
ISSN
2722-2578, 2088-8708
Published
2023-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Currently, the detection of pathology of lung cavities and their digitalization is one of the urgent problems of the healthcare industry in Kazakhstan. In this paper, the method of fractal analysis was considered to solve the task set. Diagnosis of lung pathology based on fractal analysis is an actively developing area of medical research. Conducted experiments on a set of clinical data confirm the effectiveness of the proposed methodology. The results obtained show that fractal analysis can be a useful tool for early detection of lung pathologies. It allows you to detect even minor changes in the structure and texture of lung tissues, which may not be obvious during visual analysis. The article deals with images of pathology of the pulmonary cavity, taken from an open data source. Based on the analysis of fractal objects, they were pre-assembled. Software algorithms for the operation of the information system for screening diagnostics have been developed. Based on the information contained in the fractal image of the lungs, mathematical models have been developed to create a diagnostic rule. A reference set of information features has been created that allows you to create algorithms for diagnosing the lungs: healthy and with pathologies of tuberculosis.

Collaboration network of the authors

40 authors · 202 co-authorship links · 127 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • L. N. Gumilyov Eurasian National University
  • Dulaty University
  • S.Seifullin Kazakh Agro Technical University
  • Abylkas Saginov Karaganda Technical University
  • Astana Medical University
  • Karaganda Medical University
  • Kazakh Technology and Business University named after K.Kulazhanov
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Gulmira BekmagambetovaKazakh Technology and Business University named after K.Kulazhanov5
Zhanat ManbetovaAffiliation unknown5
Gulden MurzabekovaS.Seifullin Kazakh Agro Technical University4
Makbal BaibulovaL. N. Gumilyov Eurasian National University4
Elena ZakharevichDulaty University4
Moldir YessenovaL. N. Gumilyov Eurasian National University3
Natalya GlazyrinaL. N. Gumilyov Eurasian National University3
Akbota YerzhanovaS.Seifullin Kazakh Agro Technical University2
Aigul Kayrulaevna ShaikhanovaL. N. Gumilyov Eurasian National University2
Zhanna B. SadirmekovaDulaty University2
Talgatbek AyazbaevInternational Taraz University named after Sherkhan Murtaza1
Aisulu IsmailovaS.Seifullin Kazakh Agro Technical University1
Zhanar BeldeubayevaS.Seifullin Kazakh Agro Technical University1
Aliya AinagulovaS.Seifullin Kazakh Agro Technical University1
Ayagoz MukhanovaL. N. Gumilyov Eurasian National University1
Nurbol KakabayevKokshetau State University1
Saltanat AdikanovaSarsen Amanzholov East Kazakhstan University1
Nurgul UzakkyzyL. N. Gumilyov Eurasian National University1
Rozamgul NiyazovaL. N. Gumilyov Eurasian National University1
Roza BekbayevaShakarim University1
Dinara KaibassovaAstana IT University1
Madina AldashovaL. N. Gumilyov Eurasian National University1
Aslanbek MurzakhmetovDulaty University1
Zhanar AltynbekovaKazakh National Women's Teacher Training University1
Shynar AkhmetzhanovaDulaty University1
Jamalbek TussupovL. N. Gumilyov Eurasian National University1
Gauhar BorankulovaAffiliation unknown1
Gulkiz ZhidekulovaDulaty University1
Aigul Turyszhanovna TungatarovaDulaty University1
Akgul NaizagarayevaS.Seifullin Kazakh Agro Technical University1
Natalya MutovinaAbylkas Saginov Karaganda Technical University1
Assel YerzhanAlmaty University of Power Engineering and Telecommunications1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Detection of lung pathology using the fractal method</dc:title><dc:creator>Abdikerimova, Gulzira</dc:creator><dc:creator>Shekerbek, Ainur</dc:creator><dc:creator>Tulenbayev, Murat</dc:creator><dc:creator>Sultanova, Bakhyt</dc:creator><dc:creator>Beglerova, Svetlana</dc:creator><dc:creator>Dzhaulybaeva, Elvira</dc:creator><dc:creator>Zhumakanova, Kamshat</dc:creator><dc:creator>Rysbekkyzy, Bakhytgul</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Currently, the detection of pathology of lung cavities and their digitalization is one of the urgent problems of the healthcare industry in Kazakhstan. In this paper, the method of fractal analysis was considered to solve the task set. Diagnosis of lung pathology based on fractal analysis is an actively developing area of medical research. Conducted experiments on a set of clinical data confirm the effectiveness of the proposed methodology. The results obtained show that fractal analysis can be a useful tool for early detection of lung pathologies. It allows you to detect even minor changes in the structure and texture of lung tissues, which may not be obvious during visual analysis. The article deals with images of pathology of the pulmonary cavity, taken from an open data source. Based on the analysis of fractal objects, they were pre-assembled. Software algorithms for the operation of the information system for screening diagnostics have been developed. Based on the information contained in the fractal image of the lungs, mathematical models have been developed to create a diagnostic rule. A reference set of information features has been created that allows you to create algorithms for diagnosing the lungs: healthy and with pathologies of tuberculosis. &amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-12-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v13i6.pp6778-6786</dc:identifier><dc:identifier>10.11591/ijece.v13i6.pp6778-6786</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 6 (2023); 6778</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/33451/17002</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>