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Enlarge Medical Image using Line-Column Interpolation (LCI) Method

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 5 (2018)

DOI
10.11591/ijece.v8i5.pp3620-3626
ISSN
2088-8708, 2088-8708
Published
2018-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Quality of medical image has an important role in constructing right medical diagnosis. This paper recommends a method to improve the quality of medical images by increasing the size of the image pixels. By increasing the size of pixels, the size of the objects contained therein is also greater, making it easier to observe. In this study medical images of Brain CT-Scan, Chest X-Ray and Panoramic X-Ray were processed using Line-Column Interpolation (LCI) Method. The results of the treatment are then compared to Nearest Neighbor Interpolation (NNI), Bilinear Interpolation (BLI) and Bicubic Interpolation (BCI) processing results. The experiment shows that Line-Column Interpolation Method produces a larger image with details of the objects in it are not blurred and has equal visual effects. Thus, this method is expected to be a reference material in enlarging the size of the medical image for ease in clinical analysis.

Collaboration network of the authors

16 authors · 36 co-authorship links · 12 across different organisations

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

  • Universitas Putra Indonesia "YPTK"
  • Gunadarma University
  • Universitas Baiturrahmah
  • Universitas Jember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Johan HarlanGunadarma University3
Bob Subhan RizaAffiliation unknown2
Sarifuddin MadendaGunadarma University2
Catur SuharintoUniversitas Baiturrahmah2
Ayu Widya PurnamaUniversitas Putra Indonesia "YPTK"1
Syafri ArlisUniversitas Putra Indonesia "YPTK"1
Irawadi PutraAffiliation unknown1
Romi HardiantoUniversitas Putra Indonesia "YPTK"1
Mutiana PratiwiUniversitas Putra Indonesia "YPTK"1
Surmayanti SurmayantiUniversitas Putra Indonesia "YPTK"1
Saiful BukhoriUniversitas Jember1

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>Enlarge Medical Image using Line-Column Interpolation (LCI) Method</dc:title><dc:creator>Na'am, Jufriadif</dc:creator><dc:creator>Santony, Julius</dc:creator><dc:creator>Yuhandri, Yuhandri</dc:creator><dc:creator>Sumijan, Sumijan</dc:creator><dc:creator>Nurcahyo, Gunadi Widi</dc:creator><dc:description>&lt;jats:p&gt;Quality of medical image has an important role in constructing right medical diagnosis. This paper recommends a method to improve the quality of medical images by increasing the size of the image pixels. By increasing the size of pixels, the size of the objects contained therein is also greater, making it easier to observe. In this study medical images of Brain CT-Scan, Chest X-Ray and Panoramic X-Ray were processed using Line-Column Interpolation (LCI) Method. The results of the treatment are then compared to Nearest Neighbor Interpolation (NNI), Bilinear Interpolation (BLI) and Bicubic Interpolation (BCI) processing results. The experiment shows that Line-Column Interpolation Method produces a larger image with details of the objects in it are not blurred and has equal visual effects. Thus, this method is expected to be a reference material in enlarging the size of the medical image for ease in clinical analysis.&amp;lt;br /&amp;gt;&amp;lt;br /&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2018-12-01</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.v8i5.pp3620-3626</dc:identifier><dc:identifier>10.11591/ijece.v8i5.pp3620-3626</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 8 No 5 (2018); 3620</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/12630/9724</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>