Deep caries detection using deep learning: from dataset acquisition to detection.

Journal: Clinical oral investigations
Published Date:

Abstract

OBJECTIVES: The study aims to address the global burden of dental caries, a highly prevalent disease affecting billions of individuals, including both children and adults. Recognizing the significant health challenges posed by untreated dental caries, particularly in low- and middle-income countries, our goal is to improve early-stage detection. Though effective, traditional diagnostic methods, such as bitewing radiography, have limitations in detecting early lesions. By leveraging Artificial Intelligence (AI), we aim to enhance the accuracy and efficiency of caries detection, offering a transformative approach to dental diagnostics.

Authors

  • Amandeep Kaur
    Department of Computer Science, Sri Guru Granth Sahib World University, Fatehgarh Sahib, Punjab, India.
  • Divya Jyoti
    PGIMER Satellite Centre, Gurdaspura, Sangrur, 148001, Punjab, India.
  • Ankit Sharma
    Proteomics and Coagulation Unit, Thrombosis Research Institute, Bangalore, Karnataka 560099, India.
  • Dhiraj Yelam
    Department of Computer Science, SLIET, Longowal, Sangrur, 148106, Punjab, India.
  • Rajni Goyal
    Department of Computer Science, SLIET, Longowal, Sangrur, 148106, Punjab, India.
  • Amar Nath
    Department of Computer Science, SLIET, Longowal, Sangrur, 148106, Punjab, India. amarnath@sliet.ac.in.