Deep Learning Approach for Detection of Dental Caries in X -Ray Images

Jyothi G C , Dr. Chetana Prakash , Dr. Babitha G. A , Kiran Kumar G. H.

Dental caries detection, M-FCM, Level Set, Faster R-CNN, YOLO V5, Deep Learning, X-ray images.

Dental caries is the most prevalent disease in the world, affecting more than 3.5 billion people. Dental caries must be treated, which costs money and takes time in every nation's healthcare system. Early disease detection can improve a patient's prognosis and lower the cost of treatment. X-ray imaging is the method used to detect dental caries most frequently after the visual method. A proximal and early-stage carious lesion can be easily missed by the visual examination, so X-ray imaging is very beneficial for early detection and a chance of healing without the need for additional dental care. Using M-FCM and Level Set Techniques, this paper addresses the problems of segmenting dental X-ray images and detecting caries using Faster R- CNN and YOLO V5 Deep Learning algorithms. A dataset of 1200 X-ray images with 800 dental caries annotations was generated. We used it to compare the performance of various architectures that we trained for object detection.

Published Paper   E-Certificate

"Deep Learning Approach for Detection of Dental Caries in X -Ray Images", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 6, page no.1397 - 1408, June-2023, Available :https://ijsdr.org/papers/IJSDR2306193.pdf

Volume 8 Issue 6, June-2023

Pages : 1397 - 1408

Paper Reg. ID: IJSDR_207129

Published Paper Id: IJSDR2306193

Downloads: 000347049

Research Area: Computer Science & Technology 

Country: Davangere, Karnataka, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2306193

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2306193

DOI: http://doi.one/10.1729/Journal.36206

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition