AI may accurately classify dental implant brands and estimate implant angles on panoramic radiographs

RESULTS

Among the 5 deep CNN models, the highest performance was obtained in the Visual Geometry Group (VGG)-19 model with a 98.3% accuracy rate. By applying a fusion approach based on majority voting, the accuracy rate was slightly improved to 98.9%. In addition, the root mean square error value of 2.91 degrees was obtained as a result of the regression model used in the implant angle estimation problem.

Implant images from panoramic radiographs could be classified with a high accuracy, and their angles estimated with a low mean error.

Reference:

Burcu Tiryaki, Alper Ozdogan, Mustafa Taha Guller, Ozkan Miloglu, Emin Argun Oral, Ibrahim Yucel Ozbek. Dental implant brand and angle identification using deep neural networks. The Journal of Prosthetic Dentistry. 2023. ISSN 0022-3913. https://doi.org/10.1016/j.prosdent.2023.07.022.

(https://www.sciencedirect.com/science/article/pii/S0022391323004924)

Keywords:

AI, accurately, classify, dental, implant, brands, estimate, implant, angles, panoramic radiographs, Burcu Tiryaki, Alper Ozdogan, Mustafa Taha Guller, Ozkan Miloglu, Emin Argun Oral, Ibrahim Yucel Ozbek