The Application of Mask Region-Based Convolutional Neural Networks in the Detection of Nasal Septal Deviation Using Cone Beam Computed Tomography Images: Proof-of-Concept Study
The performance of the model shows that the model is capable of detecting nasal septal deviation. Future research in this field should focus on additional preprocessing of images and detection of NSD based on multiple planes using 3D images.
Authors
- Shishir Shetty (ORCID: https://orcid.org/0000-0002-8097-6024)
- Auwalu Saleh Mubarak (ORCID: https://orcid.org/0000-0001-6240-1684)
- Sausan Al Kawas
- Wael Talaat (ORCID: https://orcid.org/0000-0002-5784-3784)
- Leena R. David (ORCID: https://orcid.org/0000-0001-5604-4764)
- Dilber Uzun Ozsahin (ORCID: https://orcid.org/0000-0002-3873-1410)
- Natheer Al‐Rawi (ORCID: https://orcid.org/0000-0002-7483-6594)
- Mhd Omar Al Jouhari (ORCID: https://orcid.org/0009-0001-6651-6080)
- Sunaina Shetty
Institutions
- University of Sharjah (AE)
- Near East University (CY)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2024-09-03
- DOI
- https://doi.org/10.2196/57335
- Citations
- 9
- Primary Topic
- Sinusitis and nasal conditions
- Type
- article
- Field-Weighted Citation Impact
- 5.22