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Improving radiologists’ and orthopedists’ QoE in diagnosing lumbar disk herniation using 3D modeling

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 11 No. 5 (2021)

DOI
10.11591/ijece.v11i5.pp4336-4344
ISSN
2722-2578, 2088-8708
Published
2021-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This article studies and analyzes the use of 3D models, built from magnetic resonance imaging (MRI) axial scans of the lumbar intervertebral disk, that are needed for the diagnosis of disk herniation. We study the possibility of assisting radiologists and orthopedists and increasing their quality of experience (QoE) during the diagnosis process. The main aim is to build a 3D model for the desired area of interest and ask the specialists to consider the 3D models in the diagnosis process instead of considering multiple axial MRI scans. We further propose an automated framework to diagnose the lumber disk herniation using the constructed 3D models. We evaluate the effectiveness of increasing the specialists QoE by conducting a questionnaire on 14 specialists with different experiences ranging from residents to consultants. We then evaluate the effectiveness of the automated diagnosis framework by training it with a set of 83 cases and then testing it on an unseen test set. The results show that the the use of 3D models increases doctors QoE and the automated framework gets 90% of diagnosis accuracy.

Collaboration network of the authors

26 authors · 70 co-authorship links · 16 across different organisations

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  • Jordan University of Science and Technology
  • Al-Zaytoonah University of Jordan
  • Yarmouk University
  • University of Southampton
  • Isra University
  • Wayne State University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Mohammed Al-SmadiAffiliation unknown4
Mahmoud HammadJordan University of Science and Technology4
Shadi Mahmoud Faleh AlZu’biAl-Zaytoonah University of Jordan4
Sa’ad A. Al-ZboonJordan University of Science and Technology3
Ghadeer Al-BdourJordan University of Science and Technology1
Raffi Al-QurranJordan University of Science and Technology1
Ali M. ShatnawiJordan University of Science and Technology1
Bashar TalafhaJordan University of Science and Technology1
Analle AbuammarUniversity of Southampton1
Yousef O. SharrabIsra University1
Bilal HawashinAl-Zaytoonah University of Jordan1
Nabil J. SarhanWayne State University1
Saja Khaled TawalbehJordan University of Science and Technology1
Amjad NuseirJordan University of Science and Technology1
Hasan AlbalasAffiliation unknown1
Aya NuseirJordan University of Science and Technology1
Maulla AlaliJordan University of Science and Technology1
Firas ZoubiAffiliation unknown1
Mohammed MahdiJordan University of Science and Technology1
Ahmad Al OmariJordan University of Science and Technology1
Wesam AlrashdanAffiliation 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 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>Improving radiologists’ and orthopedists’ QoE in diagnosing lumbar disk herniation using 3D modeling</dc:title><dc:creator>Abu Alasal, Sanaa</dc:creator><dc:creator>Alsmirat, Mohammad</dc:creator><dc:creator>Al-Mnayyis, Asma’a</dc:creator><dc:creator>Bani baker, Qanita</dc:creator><dc:creator>Al-Ayyoub, Mahmoud</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;This article studies and analyzes the use of 3D models, built from magnetic resonance imaging (MRI) axial scans of the lumbar intervertebral disk, that are needed for the diagnosis of disk herniation. We study the possibility of assisting radiologists and orthopedists and increasing their quality of experience (QoE) during the diagnosis process. The main aim is to build a 3D model for the desired area of interest and ask the specialists to consider the 3D models in the diagnosis process instead of considering multiple axial MRI scans. We further propose an automated framework to diagnose the lumber disk herniation using the constructed 3D models. We evaluate the effectiveness of increasing the specialists QoE by conducting a questionnaire on 14 specialists with different experiences ranging from residents to consultants. We then evaluate the effectiveness of the automated diagnosis framework by training it with a set of 83 cases and then testing it on an unseen test set. The results show that the the use of 3D models increases doctors QoE and the automated framework gets 90% of diagnosis accuracy.&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2021-10-01</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.v11i5.pp4336-4344</dc:identifier><dc:identifier>10.11591/ijece.v11i5.pp4336-4344</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 11 No 5 (2021); 4336</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/23143/15128</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>