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Smartphone Photogrammetric Assessment for Head Measurements
Omar C Quispe-Enriquez1, Juan José Valero-Lanzuela1, José Luis Lerma1
1Photogrammetry and Laser Scanner Research Group (GIFLE), Department of Cartographic Engineering, Geodesy and Photogrammetry, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain.
Insights
This study evaluated smartphone accuracy for infant cranial deformation assessment. The Samsung S22 series demonstrated varying precision, highlighting device choice importance for the PhotoMeDAS system.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Infant Health
Background:
- Cranial deformation assessment is vital in pediatrics and pediatric neurosurgery.
- Smartphone-based solutions like PhotoMeDAS offer accessible 3D head modeling for deformation analysis.
- Evaluating device-specific accuracy is crucial for reliable clinical application.
Purpose of the Study:
- To compare the linear accuracy of different smartphone models in generating 3D cranial models.
- To assess the performance of the PhotoMeDAS system across Samsung Galaxy S22, S22+, and S22 Ultra devices.
- To provide data for prospective users to consider device-specific accuracy in clinical settings.
Main Methods:
- Photogrammetric processing of infant head models captured by three Samsung smartphone models (S22, S22+, S22 Ultra).
- Testing three bundle adjustment implementations with and without self-calibration.
- Comparing linear accuracy against ground truth data obtained from a Creaform ACADEMIA 50 3D scanner.
Main Results:
- The Samsung S22 achieved an average accuracy of -1.15 ± 0.53 mm.
- The Samsung S22+ showed an average accuracy of 0.95 ± 0.40 mm.
- The Samsung S22 Ultra yielded an average accuracy of -1.8 ± 0.45 mm, with significant improvements noted when using a scale factor.
Conclusions:
- Smartphone model significantly impacts the accuracy of 3D cranial deformation assessment.
- The Samsung S22+ demonstrated the highest accuracy among the tested devices.
- Implementing a scale factor enhances the precision of smartphone-based photogrammetric measurements for clinical use.
Abstract:
The assessment of cranial deformation is relevant in the field of medicine dealing with infants, especially in paediatric neurosurgery and paediatrics. To address this demand, the smartphone-based solution PhotoMeDAS has been developed, harnessing mobile devices to create three-dimensional (3D) models of infants' heads and, from them, automatic cranial deformation reports. Therefore, it is crucial to examine the accuracy achievable with different mobile devices under similar conditions so prospective users can consider this aspect when using the smartphone-based solution. This study compares the linear accuracy obtained from three smartphone models (Samsung Galaxy S22 Ultra, S22, and S22+). Twelve measurements are taken with each mobile device using a coded cap on a head mannequin. For processing, three different bundle adjustment implementations are tested with and without self-calibration. After photogrammetric processing, the 3D coordinates are obtained. A comparison is made among spatially distributed distances across the head with PhotoMeDAS vs. ground truth established with a Creaform ACADEMIA 50 while-light 3D scanner. With a homogeneous scale factor for all the smartphones, the results showed that the average accuracy for the S22 smartphone is -1.15 ± 0.53 mm, for the S22+, 0.95 ± 0.40 mm, and for the S22 Ultra, -1.8 ± 0.45 mm. Worth noticing is that a substantial improvement is achieved regardless of whether the scale factor is introduced per device.
