Lojine Elbialy
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Lojine Elbialy has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Adrian Schletter
Research Center for Digital Technologies in Dentistry and CAD/CAM, Department of Dentistry, Faculty of Medicine and Dentistry, Danube Private University, Steiner Landstraße 124, 3500 Krems an der Donau, Austria
1 shared publication - Christoph Paul
Research Center for Digital Technologies in Dentistry and CAD/CAM, Department of Dentistry, Faculty of Medicine and Dentistry, Danube Private University, Steiner Landstraße 124, 3500 Krems an der Donau, Austria
1 shared publication - Constantin von See
Research Center for Digital Technologies in Dentistry and CAD/CAM, Department of Dentistry, Faculty of Medicine and Dentistry, Danube Private University, Steiner Landstraße 124, 3500 Krems an der Donau, Austria
1 shared publication - Michael Moncher
Research Center for Digital Technologies in Dentistry and CAD/CAM, Department of Dentistry, Faculty of Medicine and Dentistry, Danube Private University, Steiner Landstraße 124, 3500 Krems an der Donau, Austria
1 shared publication
Latest Publications
- Open Access
- 4 August 2026
- Published by MDPI AG in Journal of Functional Biomaterials
- Vol. 17 (8) , 384
Influence of Controlled Lighting Conditions on Smartphone-Based Augmented Reality Recognition of a 3D-Printed Dental Model for Implantological Applications
Smartphone-based augmented reality (AR) may help dentists visualize an implant axis during treatment or training. Before a virtual overlay can be displayed, however, the application must first recognize the real target reliably. This in vitro study tested how five lighting conditions affected recognition of a two-colored, 3D-printed polylactic acid (PLA) dental model by a Unity/Vuforia smartphone application. The application ran on a Samsung Galaxy S22. A GoPro HERO10 recorded the smartphone display at 240 frames per second, and the videos were evaluated frame by frame. Red, green, blue, daylight-like light-emitting diode (LED) and halogen illumination were tested at a central and an eccentric model position, with ten repetitions per condition and position. The model was not recognized under red or blue illumination within the predefined observation interval. Recognition was successful in all repetitions under green, daylight-like and halogen illumination. Recognition speed differed among these successful conditions, and the eccentric position delayed recognition under daylight-like and halogen illumination. A supplementary region-of-interest analysis also showed lighting-dependent differences in image brightness and contrast. These findings indicate that lighting should be standardized and documented when smartphone-based dental AR systems are developed and tested.
- 4 August 2026
- Published by MDPI AG in Journal of Functional Biomaterials
- Vol. 17 (8) , 384
Open AccessInfluence of Controlled Lighting Conditions on Smartphone-Based Augmented Reality Recognition of a 3D-Printed Dental Model for Implantological Applications
Smartphone-based augmented reality (AR) may help dentists visualize an implant axis during treatment or training. Before a virtual overlay can be displayed, however, the application must first recognize the real target reliably. This in vitro study tested how five lighting conditions affected recognition of a two-colored, 3D-printed polylactic acid (PLA) dental model by a Unity/Vuforia smartphone application. The application ran on a Samsung Galaxy S22. A GoPro HERO10 recorded the smartphone display at 240 frames per second, and the videos were evaluated frame by frame. Red, green, blue, daylight-like light-emitting diode (LED) and halogen illumination were tested at a central and an eccentric model position, with ten repetitions per condition and position. The model was not recognized under red or blue illumination within the predefined observation interval. Recognition was successful in all repetitions under green, daylight-like and halogen illumination. Recognition speed differed among these successful conditions, and the eccentric position delayed recognition under daylight-like and halogen illumination. A supplementary region-of-interest analysis also showed lighting-dependent differences in image brightness and contrast. These findings indicate that lighting should be standardized and documented when smartphone-based dental AR systems are developed and tested.