Deep Metric Learning For Teeth Classification

Abstract

The Proposed System Is A Deep Learning-based Dental Image Classification Tool That Uses Deep Metric Learning Techniques For Accuratedental Conditions Identification, Such As Cavities, Implants, Fillings, Implanted Teeth, Impacted Teeth, And Root Canals Play A Critical Role In The Early Diagnosis And Treatment Planning In Dentistry. This Project Proposes An Automated, Deep Learning-based Solution For Teeth Classification Using Image Processing And Deep Metric Learning Techniques. Leveraging DenseNet121, The System Is Trained To Detect And Classify Various Dental Conditions Identification With High Accuracy. The Classification Is Achieved Through A Well-defined Pipeline Involving Image Preprocessing, Segmentation, Image Splitting, And Feature Extraction, Enabling The Model To Handle Variability In Image Quality And Tooth Structure.The System Is Deployed As A User-friendly Web Application Built Using Streamlit, Allowing Users To Register, Log In, And Upload Dental Images For Instant Classification Results. The Application Processes The Image, Classifies The Dental Condition, And Displays Performance Metrics Such As Accuracy, Confusion Matrix, And ROC Curve. This Solution Aims To Assist Dental Professionals, Researchers, And, In Forensic Cases, By Providing An Accessible Tool For Image-based Dental Condition Identification, Thus Enhancing Clinical Decision-making Through Automated And Efficient Image Analysis.

Keywords