Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Computed tomography scans image processing for nasal symptoms severity prediction

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 2 (2022)

DOI
10.11591/ijece.v12i2.pp1488-1497
ISSN
2722-2578, 2088-8708
Published
2022-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This paper aims to use a new technique of computed tomography (CT) scan image processing to correlate the image analysis with sinonasal symptoms. A retrospective cross-sectional study is conducted by analyzing the digital records of 50 patients who attended the ear, nose and throat (ENT) clinics at King Abdullah University Hospital, Jordan. The coronal plane CT scans are analyzed using our developed software. The purposes of this software are to calculate the surface area of the nasal passage at three different levels visible on coronal plane CT scans: i) the head of the inferior turbinate, ii) the head of the middle turbinate, and iii) the tail of the inferior turbinate. We employ image processing techniques to correlate the narrowing of nasal surface area with sinonasal symptoms. As a consequence, obstruction in the first level is correlated significantly with the symptoms of nasal obstruction while the narrowing in the second level is related to frontal headache. No other significant correlations are found with nasal symptoms at the third level. In our study, we find that image processing techniques can be very useful to predict the severity of common nasal symptoms and they can be used to suggest treatment and to follow up on the case progression.

Collaboration network of the authors

17 authors · 47 co-authorship links · 6 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
  • University of Southampton
  • Yarmouk University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
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
Asma’a Al-MnayyisYarmouk University1
Sanaa Abu AlasalJordan University of Science and Technology1
Mohammad A. AlsmiratJordan University of Science and Technology1
Qanita Bani BakerJordan University of Science and Technology1

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>Computed tomography scans image processing for nasal symptoms severity prediction</dc:title><dc:creator>Nuseir, Amjad</dc:creator><dc:creator>Albalas, Hasan</dc:creator><dc:creator>Nuseir, Aya</dc:creator><dc:creator>Alali, Maulla</dc:creator><dc:creator>Zoubi, Firas</dc:creator><dc:creator>Al-Ayyoub, Mahmoud</dc:creator><dc:creator>Mahdi, Mohammed</dc:creator><dc:creator>Al Omari, Ahmad</dc:creator><dc:description>&lt;jats:p&gt;This paper aims to use a new technique of computed tomography (CT) scan image processing to correlate the image analysis with sinonasal symptoms. A retrospective cross-sectional study is conducted by analyzing the digital records of 50 patients who attended the ear, nose and throat (ENT) clinics at King Abdullah University Hospital, Jordan. The coronal plane CT scans are analyzed using our developed software. The purposes of this software are to calculate the surface area of the nasal passage at three different levels visible on coronal plane CT scans: i) the head of the inferior turbinate, ii) the head of the middle turbinate, and iii) the tail of the inferior turbinate. We employ image processing techniques to correlate the narrowing of nasal surface area with sinonasal symptoms. As a consequence, obstruction in the first level is correlated significantly with the symptoms of nasal obstruction while the narrowing in the second level is related to frontal headache. No other significant correlations are found with nasal symptoms at the third level. In our study, we find that image processing techniques can be very useful to predict the severity of common nasal symptoms and they can be used to suggest treatment and to follow up on the case progression.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-04-01</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.v12i2.pp1488-1497</dc:identifier><dc:identifier>10.11591/ijece.v12i2.pp1488-1497</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 2 (2022); 1488</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/25894/15502</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>