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Preliminary process in blast cell morphology identification based on image segmentation methods

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 6 (2020)

DOI
10.11591/ijece.v10i6.pp5714-5725
ISSN
2722-2578, 2088-8708
Published
2020-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The diagnosis of blood disorders in developing countries usually uses the diagnostic procedure Complete Blood Count (CBC). This is due to the limitations of existing health facilities so that examinations use standard microscopes as required in CBC examinations. However, the CBC process still poses a problem, namely that the procedure for manually counting blood cells with a microscope requires a lot of energy and time, and is expensive. This paper will discuss alternative uses of image processing technology in blast cell identification by using microscope images. In this paper, we will discuss in detail the morphological measurements which include the diameter, circumference and area of blast cell cells based on watershed segmentation methods and active contour. As a basis for further development, we compare the performance between the uses of both methods. The results show that the active contour method has an error percentage of 5.15% while the watershed method has an error percentage of 8.25%.

Collaboration network of the authors

13 authors · 39 co-authorship links · 6 across different organisations

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  • Jenderal Soedirman University
  • Nara Institute of Science and Technology
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Haris Budi WidodoJenderal Soedirman University8
Ariep Soelaiman SetiadiJenderal Soedirman University4
Alfin ChrisantyJenderal Soedirman University3
Muhammad Rifqi KurniawanJenderal Soedirman University2
Arif Pujo RiyantoJenderal Soedirman University2
Muhammad Syaiful AliimJenderal Soedirman University2
Muhammad Irham AkbarJenderal Soedirman University2
Muhammad AlqaafNara Institute of Science and Technology2

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 1 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>Preliminary process in blast cell morphology identification based on image segmentation methods</dc:title><dc:creator>Supriyanti, Retno</dc:creator><dc:creator>Wibowo, Pangestu F.</dc:creator><dc:creator>Firmanda, Fibra R.</dc:creator><dc:creator>Ramadhani, Yogi</dc:creator><dc:creator>Siswandari, Wahyu</dc:creator><dc:description>&lt;jats:p&gt;The diagnosis of blood disorders in developing countries usually uses the diagnostic procedure Complete Blood Count (CBC). This is due to the limitations of existing health facilities so that examinations use standard microscopes as required in CBC examinations. However, the CBC process still poses a problem, namely that the procedure for manually counting blood cells with a microscope requires a lot of energy and time, and is expensive. This paper will discuss alternative uses of image processing technology in blast cell identification by using microscope images. In this paper, we will discuss in detail the morphological measurements which include the diameter, circumference and area of blast cell cells based on watershed segmentation methods and active contour. As a basis for further development, we compare the performance between the uses of both methods. The results show that the active contour method has an error percentage of 5.15% while the watershed method has an error percentage of 8.25%.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-12-01</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.v10i6.pp5714-5725</dc:identifier><dc:identifier>10.11591/ijece.v10i6.pp5714-5725</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 6 (2020); 5714</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/21873/14355</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>