Integration and Application of Multimodal Measurement Techniques: Relevance of Photogrammetry to Orthodontics

Single-camera photogrammetry using a mobile phone for low-cost documentation of corpses

Photogrammetry is a technique for studying and defining objects' shape, dimension, and position in a three-dimensional space using measurements obtained from two-dimensional photographs. It has gained popularity following the development of computer graphics technologies and has been applied to various branches of medicine. In this study, the authors present a method for low-cost photorealistic documentation of corpses during autopsy using single-camera photogrammetry with a mobile phone. Besides representing the body by demonstrating the injured and non-injured body parts as control, evidencing the body parts on a 3D reconstruction allows easy explanation to nonmedical experts such as lawyers.

A comparative evaluation of photogrammetry software programs and conventional impression techniques for the fabrication of nasal maxillofacial prostheses

STATEMENT OF PROBLEM

The fabrication of facial prostheses is complicated and time-consuming because of the need for accurate impressions of the facial defects and surrounding tissues. Inaccuracies can arise from soft-tissue compression, involuntary patient movements, and insufficient support for the impression material. Various 3-dimensional (3D) imaging and scanning techniques, including photogrammetry, have been introduced, but their accuracy remains insufficiently evaluated.

PURPOSE

The purpose of this in vitro study was to evaluate and compare the accuracy of 3D digital casts generated by 4 photogrammetry software programs (Agisoft Metashape, 3DF Zephyr, Meshroom, and Polycam) and casts from 2 conventional impression materials (alginate and polyvinyl siloxane [PVS]) for the fabrication of nasal maxillofacial prostheses.

MATERIAL AND METHODS

A stone cast of a patient's nose was used as the basis for generating a reference digital 3D cast and another 54 test 3D casts. The reference cast was created by scanning the stone cast using a FARO Optor Lab 3D scanner. The 54 test 3D casts were generated and divided into 6 test groups as follows: Agisoft group: 9 3D casts generated using Agisoft Metashape, a commercial personal computer (PC) software program; 3DF Zephyr group: 9 3D casts generated using 3DF Zephyr, a commercial PC software program; Meshroom group: 9 3D casts generated using Meshroom, a free PC software program; Polycam group: 9 3D casts generated using the Polycam, a commercial Android cloud application; PVS group: 9 3D casts generated indirectly by 3D scanning a gypsum cast made from a polyvinyl siloxane (PVS) impression of the stone nose cast; and Alginate group: 9 3D casts generated indirectly by scanning a master cast made using alginate impressions of the stone nose cast. Deviation measurements of the produced specimens were analyzed using the Geomagic Control X software program, and statistical comparisons were performed employing the Kruskal-Wallis test (α=.05).

RESULTS

The results showed that the 3DF Zephyr group had the smallest deviation measurements (median: 0.057 mm ±0.012) among the 4 photogrammetry software programs, while the alginate impression group had the largest deviations (median: 0.151 mm ±0.094) of the 2 conventional impression materials. Significant differences were observed among the 4 photogrammetry software programs and the 2 conventional impression materials (H=39.41, df=5, P<.001). The casts generated by Agisoft Metashape were significantly more accurate than those produced by Meshroom, Polycam or the conventional impression materials (P=.024, P=.045, P<.001, respectively). The casts produced by 3DF Zephyr were significantly more precise than those created by Meshroom and the conventional impression materials (P=.037, P<.001, respectively). No significant differences were observed between the Agisoft Metashape and 3DF Zephyr groups (P>.05).

CONCLUSIONS

Photogrammetry software programs, specifically Agisoft Metashape and 3DF Zephyr, demonstrated better accuracy than conventional impression materials in creating nasal digital casts. Photogrammetry has the potential to improve workflow and reduce patient discomfort during the fabrication of maxillofacial prostheses. Further research is needed to validate these findings in clinical settings.

Validity and reliability of three-dimensional modeling of orthodontic dental casts using smartphone-based photogrammetric technology

BACKGROUND

The development of intraoral scanning technology has effectively enhanced the digital documentation of orthodontic dental casts. Albeit, the expense of this technology is the main limitation. The purpose of the present study was to assess the validity and reliability of virtual three-dimensional (3D) models of orthodontic dental casts, which were constructed using smartphone-based 3D photogrammetry.

METHODS

A smartphone was used to capture a set of two-dimensional images for 30 orthodontic dental casts. The captured images were processed to construct 3D virtual images using Agisoft and 3DF Zephyr software programs. To evaluate the accuracy of the virtual 3D models obtained by the two software programs, the virtual 3D models were compared with cone-beam computed tomography scans of the 30 dental casts. Colored maps were used to express the absolute distances between the points of each compared two surfaces; then, the means of the 100%, 95th, and 90th of the absolute distances were calculated. A Wilcoxon signed-rank test was applied to detect any significant differences.

RESULTS

The differences between the constructed 3D images and the cone-beam computed tomography scans were not statistically significant and were accepted clinically. The deviations were mostly in the interproximal areas and in the occlusal details (sharp cusps and deep pits and fissures).

CONCLUSIONS

This study found that smartphone-based stereophotogrammetry is an accurate and reliable method for 3D modeling of orthodontic dental casts, with errors less than the accepted clinically detectable error of 0.5 mm. Smartphone photogrammetry succeeded in presenting occlusal details, but it was difficult to accurately reproduce interproximal areas.

Analysis of the Influence of the Geometrical Parameters of the Body Scanner on the Accuracy of Reconstruction of the Human Figure Using the Photogrammetry Technique

This article concerns the research of the HUBO full-body scanner, which includes the analysis and selection of the scanner's geometrical parameters in order to obtain the highest possible accuracy of the reconstruction of a human figure. In the scanner version analyzed in this paper, smartphone cameras are used as sensors. In order to process the collected photos into a 3D model, the photogrammetry technique is applied. As part of the work, dependencies between the geometrical parameters of the scanner are derived, which allows to significantly reduce the number of degrees of freedom in the selection of its geometrical parameters. Based on these dependencies, a numerical analysis is carried out, as a result of which the initial values of the geometrical parameters are pre-selected and distribution of scanner cameras is visualized. As part of the experimental research, the influence of selected scanner parameters on the scanning accuracy is analyzed. For the experimental research, a specially prepared dummy was used instead of the participation of a real human, which allowed to ensure the constancy of the scanned object. The accuracy of the object reconstruction was assessed in relation to the reference 3D model obtained with a scanner of superior measurement uncertainty. On the basis of the conducted research, a method for the selection of the scanner's geometrical parameters was finally verified, leading to the arrangement of cameras around a human, which guarantees high accuracy of the reconstruction. Additionally, to quantify the results, the quality rates were used, taking into account not only the obtained measurement uncertainty of the scanner, but also the processing time and the resulting efficiency.

Smartphone-Based Facial Scanning as a Viable Tool for Facially Driven Orthodontics?

The current paradigm shift in orthodontic treatment planning is based on facially driven diagnostics. This requires an affordable, convenient, and non-invasive solution for face scanning. Therefore, utilization of smartphones' TrueDepth sensors is very tempting. TrueDepth refers to front-facing cameras with a dot projector in Apple devices that provide real-time depth data in addition to visual information. There are several applications that tout themselves as accurate solutions for 3D scanning of the face in dentistry. Their clinical accuracy has been uncertain. This study focuses on evaluating the accuracy of the Bellus3D Dental Pro app, which uses Apple's TrueDepth sensor. The app reconstructs a virtual, high-resolution version of the face, which is available for download as a 3D object. In this paper, sixty TrueDepth scans of the face were compared to sixty corresponding facial surfaces segmented from CBCT. Difference maps were created for each pair and evaluated in specific facial regions. The results confirmed statistically significant differences in some facial regions with amplitudes greater than 3 mm, suggesting that current technology has limited applicability for clinical use. The clinical utilization of facial scanning for orthodontic evaluation, which does not require accuracy in the lip region below 3 mm, can be considered.

Low-Cost Method for 3D Body Measurement Based on Photogrammetry Using Smartphone

This paper is focused on the possibilities of data collection via photogrammetry methods, using smartphone cameras and post-processing. The aim of this paper is to refer to progressive technologies that are part of smartphone devices, which bring more performance and variability of usage year by year. The theoretical part starts with looking to the past, describing problems of measurements and solutions invented by famous mathematicians, which we use nowadays. The following section deals with the background of measuring the human body and photogrammetry. The next section is about measuring and using calibration methods. The results section presents the architecture design of the system and a visual representation of how the application works. The result of processing a 3D person is a data object with measurements in real world metric units with minimum deviation. The conclusion is that we created our own low-cost method for 3D body measurement which partially or completely removes the shortcomings that were identified during the review of similar solutions. Our method is based on the use of open-source libraries, the use of a single smartphone mobile device and the creation of a true 3D human body model.