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Calculating the area of white spots on the lungs of patients with COVID-19 using the Sauvola thresholding method

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 1 (2023)

DOI
10.11591/ijece.v13i1.pp315-324
ISSN
2722-2578, 2088-8708
Published
2023-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

COVID-19 is a pandemic that has occurred in the world since 2019. Researchers have carried out various ways in dealing with this disease, starting from the screening stage to the stage of treatment and therapy for COVID-19 patients. As the gateway to the COVID-19 problem, screening has an essential role in a diagnosis that leads to appropriate treatment. In this paper, we will focus on the screening stage using digital image processing techniques, namely in calculating the area of white spots in the lungs of COVID-19 patients. The white patches are an early indication of how badly COVID-19 is attacking the patient. We use X-Ray Thorax image objects as research data in this paper. Although the current experimental results show that this method has a successful performance of 71.11%, it is pretty promising for further development due to its simplicity.

Collaboration network of the authors

40 authors · 132 co-authorship links · 9 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.

  • Jenderal Soedirman University
  • Nara Institute of Science and Technology
  • Institut Agama Islam Negeri Ternate
  • Institut Teknologi Telkom Purwokerto
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Muhammad AlqaafNara Institute of Science and Technology8
Ariep Soelaiman SetiadiJenderal Soedirman University6
Wahyu WidanartoAffiliation unknown5
Wahyu SiswandariJenderal Soedirman University4
Suroso SurosoAffiliation unknown3
Arif Pujo RiyantoJenderal Soedirman University3
Muhammad Syaiful AliimJenderal Soedirman University3
Muhammad Irham AkbarJenderal Soedirman University3
Dina RahmawatiInstitut Agama Islam Negeri Ternate2
Syafrudin Rais AkhdanAffiliation unknown2
Alfin ChrisantyJenderal Soedirman University2
Pangestu F. WibowoJenderal Soedirman University2
Fibra R. FirmandaJenderal Soedirman University2
Arsil Kultura AnzilAffiliation unknown2
Kartika Dwi HapsariAffiliation unknown2
Futiat Diana KartikaAffiliation unknown2
Anung SaptiwulanAffiliation unknown1
Helmi HirawanAffiliation unknown1
Christiana Cahyani PrihastutiAffiliation unknown1
Tirta WardanaAffiliation unknown1
Dody NovrialAffiliation unknown1
Restian Febi AndiniAffiliation unknown1
Agi PrasetiadiInstitut Teknologi Telkom Purwokerto1
Andre Citro Febriliyan LanyakAffiliation unknown1
Muhammad Hisyam GhaniAffiliation unknown1
Abiyan AthallahAffiliation unknown1
Andreas S. AryantoAffiliation unknown1
Mohammad Irham AkbarAffiliation unknown1
Eman SutrisnaAffiliation unknown1
Winasis WinasisAffiliation unknown1
Rafi Satria Dwi AwandaAffiliation unknown1
Madya Ardi WicaksonoAffiliation unknown1
Putra Dwi SusantoAffiliation unknown1
Madya Ardi WicaksonoAffiliation unknown1
Mukhtar EffendiAffiliation unknown1
Tomy TamtowiAffiliation unknown1

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 Oct 2026, last seen 8 Nov 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>Calculating the area of white spots on the lungs of patients with COVID-19 using the Sauvola thresholding method</dc:title><dc:creator>Supriyanti, Retno</dc:creator><dc:creator>Kurniawan, Muhammad Rifqi</dc:creator><dc:creator>Ramadhani, Yogi</dc:creator><dc:creator>Widodo, Haris Budi</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;COVID-19 is a pandemic that has occurred in the world since 2019. Researchers have carried out various ways in dealing with this disease, starting from the screening stage to the stage of treatment and therapy for COVID-19 patients. As the gateway to the COVID-19 problem, screening has an essential role in a diagnosis that leads to appropriate treatment. In this paper, we will focus on the screening stage using digital image processing techniques, namely in calculating the area of white spots in the lungs of COVID-19 patients. The white patches are an early indication of how badly COVID-19 is attacking the patient. We use X-Ray Thorax image objects as research data in this paper. Although the current experimental results show that this method has a successful performance of 71.11%, it is pretty promising for further development due to its simplicity.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-02-01</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.v13i1.pp315-324</dc:identifier><dc:identifier>10.11591/ijece.v13i1.pp315-324</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 1 (2023); 315</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/27248/16199</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>