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TVGG Dental Implant Identification System

Authors :
Jianbin Guo
Pei-Wei Tsai
Xingsi Xue
Dong Wu
Qui Tran Van
Chanaka Nimantha Kaluarachchi
Hong Thi Dang
Nikhitha Chintha
Source :
Frontiers in Pharmacology, Vol 13 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

Identifying the right accessories for installing the dental implant is a vital element that impacts the sustainability and the reliability of the dental prosthesis when the medical case of a patient is not comprehensive. Dentists need to identify the implant manufacturer from the x-ray image to determine further treatment procedures. Identifying the manufacturer is a high-pressure task under the scaling volume of patients pending in the queue for treatment. To reduce the burden on the doctors, a dental implant identification system is built based on a new proposed thinner VGG model with an on-demand client-server structure. We propose a thinner version of VGG16 called TVGG by reducing the number of neurons in the dense layers to improve the system’s performance and gain advantages from the limited texture and patterns in the dental radiography images. The outcome of the proposed system is compared with the original pre-trained VGG16 to verify the usability of the proposed system.

Details

Language :
English
ISSN :
16639812
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Pharmacology
Publication Type :
Academic Journal
Accession number :
edsdoj.9693d9dc498043d98a0f652464c4652f
Document Type :
article
Full Text :
https://doi.org/10.3389/fphar.2022.948283