Deep Learning for Dental Diagnosis: A Novel Approach to Furcation Involvement Detection on Periapical Radiographs

• Main Authors: Mao, Yi Cheng, Huang, Yen Cheng, Chen, Tsung Yi, Li, Kuo Chen, Lin, Yuan Jin, Liu, Yu Lin, Yan, Hong Rong, Yang, Yu Jie, Chen, Chiung An, Chen, Shih Lun, Li, Chun Wei, Chan, Mei Ling, Chuo, Yueh, Abu, Patricia Angela R
• Format: text
• Published: Archīum Ateneo 2023
• Subjects: CNN; deep learning; furcation involvement; Gaussian high-pass filtering; image preprocessing; image segmentation; periapical radiograph; Biomedical; Biomedical Engineering and Bioengineering; Computer Engineering; Electrical and Computer Engineering; Engineering
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/371; https://drive.google.com/file/d/1bgW5CANaf0172EX1PqyazsMgf62v0xKJ/view?usp=sharing
• Institution: Ateneo De Manila University

Furcation defects pose a significant challenge in the diagnosis and treatment planning of periodontal diseases. The accurate detection of furcation involvements (FI) on periapical radiographs (PAs) is crucial for the success of periodontal therapy. This research proposes a deep learning-based approa...