Classification of Dental Radiographs Using Deep Learning
Objectives: To retrospectively assess radiographic data and to prospectively classify radiographs (namely, panoramic, bitewing, periapical, and cephalometric images), we compared three deep learning architectures for their classification performance. Methods: Our dataset consisted of 31,288 panorami...
Main Authors: | Jose E. Cejudo, Akhilanand Chaurasia, Ben Feldberg, Joachim Krois, Falk Schwendicke |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-04-01
|
Series: | Journal of Clinical Medicine |
Subjects: | |
Online Access: | https://www.mdpi.com/2077-0383/10/7/1496 |
Similar Items
-
Multi-Task Deep Learning Model for Classification of Dental Implant Brand and Treatment Stage Using Dental Panoramic Radiograph Images
by: Shintaro Sukegawa, et al.
Published: (2021-05-01) -
Transfer Learning via Deep Neural Networks for Implant Fixture System Classification Using Periapical Radiographs
by: Jong-Eun Kim, et al.
Published: (2020-04-01) -
Impact of Image Context on Deep Learning for Classification of Teeth on Radiographs
by: Joachim Krois, et al.
Published: (2021-04-01) -
Deep Neural Networks for Dental Implant System Classification
by: Shintaro Sukegawa, et al.
Published: (2020-07-01) -
Automating classification of osteoarthritis according to Kellgren-Lawrence in the knee using deep learning in an unfiltered adult population
by: Simon Olsson, et al.
Published: (2021-10-01)