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Lumbar disk 3D modeling from limited number of MRI axial slices

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 4 (2020)

DOI
10.11591/ijece.v10i4.pp4101-4108
ISSN
2722-2578, 2088-8708
Published
2020-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

This paper studies the problem of clinical MRI analysis in the field of lumbar intervertebral disk herniation diagnosis. It discusses the possibility of assisting radiologists in reading the patients MRI images by constructing a 3D model for the region of interest using simple computer vision methods. We use axial MRI slices of the lumbar area. The proposed framework works with a very small number of MRI slices and goes through three main stages. Namely, the region of interest extraction and enhancement, inter-slice interpolation, and 3D model construction. We use the Marching Cubes algorithm to construct the 3D model of the the region of interest. The validation of our 3D models is based on a radiologist’s analysis of the models. We tested the proposed 3D model construction on 83 cases and We have a 95% accuracy according to the radiologist evaluation. This study shows that 3D model construction can greatly ease the task of the radiologist which enhances the working experience. This leads eventually to more accurate and easy diagnosis process.

Collaboration network of the authors

14 authors · 33 co-authorship links · 14 across different organisations

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

  • Jordan University of Science and Technology
  • Al-Zaytoonah University of Jordan
  • Yarmouk University
  • 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
Mahmoud Al‐AyyoubJordan University of Science and Technology4
Sa’ad A. Al-ZboonJordan University of Science and Technology3
Yousef O. SharrabIsra University1
Bilal HawashinAl-Zaytoonah University of Jordan1
Nabil J. SarhanWayne State University1
Saja Khaled TawalbehJordan 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>Lumbar disk 3D modeling from limited number of MRI axial slices</dc:title><dc:creator>Al-Mnayyis, Asma’a</dc:creator><dc:creator>Alasal, Sanaa Abu</dc:creator><dc:creator>Alsmirat, Mohammad</dc:creator><dc:creator>Baker, Qanita Bani</dc:creator><dc:creator>AlZu’bi, Shadi</dc:creator><dc:description>&lt;jats:p&gt;This paper studies the problem of clinical MRI analysis in the field of lumbar intervertebral disk herniation diagnosis. It discusses the possibility of assisting radiologists in reading the patients MRI images by constructing a 3D model for the region of interest using simple computer vision methods. We use axial MRI slices of the lumbar area. The proposed framework works with a very small number of MRI slices and goes through three main stages. Namely, the region of interest extraction and enhancement, inter-slice interpolation, and 3D model construction. We use the Marching Cubes algorithm to construct the 3D model of the the region of interest. The validation of our 3D models is based on a radiologist’s analysis of the models. We tested the proposed 3D model construction  on 83  cases and We have a 95% accuracy according to the radiologist evaluation. This study shows that 3D model construction can greatly ease the task of the radiologist which enhances the working experience. This leads eventually to more accurate and easy diagnosis process.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-08-01</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.v10i4.pp4101-4108</dc:identifier><dc:identifier>10.11591/ijece.v10i4.pp4101-4108</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 4 (2020); 4101</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/21516/14092</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>