Estimating Maxillary Sinus Volume Using Smartphone Camera

<i>Goal:</i> This study aims to introduce a novel method for estimating maxillary sinus volume using smartphone technology, providing an accessible alternative to traditional imaging techniques. <i>Methods:</i> We recruited 40 participants to conduct a comparative analysis between Computed Tomography (CT) and face scans obtained using an Apple iPhone. Utilizing Apple's ARKit for 3D facial mesh modeling, we estimated sinus dimensions based on established craniofacial landmarks and calculated the volume through a geometric approximation of the maxillary sinus. <i>Results:</i> We demonstrated a high degree of agreement between CT and face scans, with Mean Absolute Percentage Errors (MAPE) of 8.006 ± 8.839% (Width), 6.725 ± 4.595% (Height), 9.952 ± 6.733% (Depth), and 10.429 ± 7.409% (Volume). These results suggest the feasibility of this non-invasive approach for clinical use. <i>Conclusions:</i> This method aligns with the growing focus on telemedicine, presenting significant reductions in healthcare costs and radiation exposure from CT scans. It marks a substantial advancement in otolaryngology and maxillofacial surgery, showcasing the integration of smartphone technology in medical diagnostics and opening avenues for innovative, patient-friendly, and cost-effective healthcare solutions.

Authors

Institutions

Publication Details

Journal
IEEE Open Journal of Engineering in Medicine and Biology
Published
2024-12-12
DOI
https://doi.org/10.1109/ojemb.2024.3516320
Citations
3
Primary Topic
Nasal Surgery and Airway Studies
Type
article
Field-Weighted Citation Impact
1.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimating Maxillary Sinus Volume Using Smartphone Camera

Jacob Johnson, Wendy Zhu, Emily Feng, Ezekiel Johnson et al.
3 citations
IEEE Open Journal of Engineering in Medicine and Biology
Nasal Surgery and Airway Studies
1.72
article

Estimating Maxillary Sinus Volume Using Smartphone Camera

Jacob Johnson, Wendy Zhu, Emily Feng, Ezekiel Johnson, Vivek Mohan, Peter H. Hwang, Bryant Lin, P G Gopi, Christoforos Meliadis
article en
3 citations

Abstract

<i>Goal:</i> This study aims to introduce a novel method for estimating maxillary sinus volume using smartphone technology, providing an accessible alternative to traditional imaging techniques. <i>Methods:</i> We recruited 40 participants to conduct a comparative analysis between Computed Tomography (CT) and face scans obtained using an Apple iPhone. Utilizing Apple's ARKit for 3D facial mesh modeling, we estimated sinus dimensions based on established craniofacial landmarks and calculated the volume through a geometric approximation of the maxillary sinus. <i>Results:</i> We demonstrated a high degree of agreement between CT and face scans, with Mean Absolute Percentage Errors (MAPE) of 8.006 ± 8.839% (Width), 6.725 ± 4.595% (Height), 9.952 ± 6.733% (Depth), and 10.429 ± 7.409% (Volume). These results suggest the feasibility of this non-invasive approach for clinical use. <i>Conclusions:</i> This method aligns with the growing focus on telemedicine, presenting significant reductions in healthcare costs and radiation exposure from CT scans. It marks a substantial advancement in otolaryngology and maxillofacial surgery, showcasing the integration of smartphone technology in medical diagnostics and opening avenues for innovative, patient-friendly, and cost-effective healthcare solutions.

IEEE Open Journal of Engineering in Medicine and BiologyVol. 6
University of California, San Francisco (US), Stanford University (US)
Affordable and clean energy
Openalex Percentile: Top 14%
Nasal Surgery and Airway Studies
1.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Estimating Maxillary Sinus Volume Using Smartphone Camera — Jacob Johnson, Wendy Zhu, et al. · IEEE Open Journal of Engineering in Medicine and Biology (2024) | TGRS Research Map | TGRS