Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

An effective RGB color selection for complex 3D object structure in scene graph systems

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

DOI
10.11591/ijece.v10i6.pp5951-5964
ISSN
2722-2578, 2088-8708
Published
2020-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The goal of this project is to develop a complete, fully detailed 3D interactive model of the human body and systems in the human body, and allow the user to interacts in 3D with all the elements of that system, to teach students about human anatomy. Some organs, which contain a lot of details about a particular anatomy, need to be accurately and fully described in minute detail, such as the brain, lungs, liver and heart. These organs are need have all the detailed descriptions of the medical information needed to learn how to do surgery on them, and should allow the user to add careful and precise marking to indicate the operative landmarks on the surgery location. Adding so many different items of information is challenging when the area to which the information needs to be attached is very detailed and overlaps with all kinds of other medical information related to the area. Existing methods to tag areas was not allowing us sufficient locations to attach the information to. Our solution combines a variety of tagging methods, which use the marking method by selecting the RGB color area that is drawn in the texture, on the complex 3D object structure. Then, it relies on those RGB color codes to tag IDs and create relational tables that store the related information about the specific areas of the anatomy. With this method of marking, it is possible to use the entire set of color values (R, G, B) to identify a set of anatomic regions, and this also makes it possible to define multiple overlapping regions.

Collaboration network of the authors

11 authors · 31 co-authorship links · 29 across different organisations

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

  • Duy Tan University
  • Huế University of Medicine and Pharmacy
  • Hai Phong University
  • Hooghly Engineering & Technology College
  • University of Kalyani
  • University of Calcutta
  • Techno India University
  • Other organisations
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Sirshendu HoreHooghly Engineering & Technology College2
Souvik ChakrabortyUniversity of Kalyani2
Sankhadeep ChatterjeeUniversity of Calcutta2
Nilanjan DeyTechno India University2
Amira Salah AshourTanta University2
Le Van ChungDuy Tan University2

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>An effective RGB color selection for complex 3D object structure in scene graph systems</dc:title><dc:creator>Van, Chung Le</dc:creator><dc:creator>Nguyen, Gia Nhu</dc:creator><dc:creator>Nguyen, Tri Huu</dc:creator><dc:creator>Nguyen, Tung Sanh</dc:creator><dc:creator>Le, Dac-Nhuong</dc:creator><dc:description>&lt;jats:p&gt;The goal of this project is to develop a complete, fully detailed 3D interactive model of the human body and systems in the human body, and allow the user to interacts in 3D with all the elements of that system, to teach students about human anatomy. Some organs, which contain a lot of details about a particular anatomy, need to be accurately and fully described in minute detail, such as the brain, lungs, liver and heart. These organs are need have all the detailed descriptions of the medical information needed to learn how to do surgery on them, and should allow the user to add careful and precise marking to indicate the operative landmarks on the surgery location. Adding so many different items of information is challenging when the area to which the information needs to be attached is very detailed and overlaps with all kinds of other medical information related to the area. Existing methods to tag areas was not allowing us sufficient locations to attach the information to. Our solution combines a variety of tagging methods, which use the marking method by selecting the RGB color area that is drawn in the texture, on the complex 3D object structure. Then, it relies on those RGB color codes to tag IDs and create relational tables that store the related information about the specific areas of the anatomy. With this method of marking, it is possible to use the entire set of color values (R, G, B) to identify a set of anatomic regions, and this also makes it possible to define multiple overlapping regions.&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.pp5951-5964</dc:identifier><dc:identifier>10.11591/ijece.v10i6.pp5951-5964</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 6 (2020); 5951</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/22118/14391</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>