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                            Library & Multimedia
 Tufts Dental Database: A Multimodal Panoramic X-Ray Dataset for Benchmarking Diagnostic Systems
NCJ Number
              304973

Author(s)
          Panetta, K.;
                        Rajendran, R.;
                        Ramesh, A.;
                        Rao, S.;
                        Agaian, S.
Date Published

April 2022
Length
              10 pages
Annotation
              The Tufts Dental Database, a new X-ray panoramic radiography image database is presented in this paper.
Abstract
              This dataset consists of 1000 panoramic dental radiography images with expert labeling of abnormalities and teeth. The classification of radiography images was performed based on five different levels: anatomical location, peripheral characteristics, radiodensity, effects on the surrounding structure, and the abnormality category. This first-of-its-kind multimodal dataset also includes the radiologist's expertise captured in the form of eye-tracking and think-aloud protocol. The contributions of this work are 1) publicly available dataset that can help researchers to incorporate human expertise into AI and achieve more robust and accurate abnormality detection; 2) a benchmark performance analysis for various state-of-the-art systems for dental radiograph image enhancement and image segmentation using deep learning; 3) an in-depth review of various panoramic dental image datasets, along with segmentation and detection systems. The release of this dataset aims to propel the development of AI-powered automated abnormality detection and classification in dental panoramic radiographs, enhance tooth segmentation algorithms, and the ability to distill the radiologist's expertise into AI. The application of Artificial Intelligence in dental healthcare has a very promising role due to the abundance of imagery and non-imagery-based clinical data. Expert analysis of dental radiographs can provide crucial information for clinical diagnosis and treatment. In recent years, Convolutional Neural Networks have achieved the highest accuracy in various benchmarks, including analyzing dental X-ray images to improve clinical care quality. (Publisher Abstract Provided)
      
  
          Additional Details
Grant Number(s)
        2019-R2-CX-0036


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Award
        Developing, Visualization, and Reporting a Combined 2D+3D Automated Dental Biometrics Identification System for Forensic Odontology
    
  
  
Date Published: April 1, 2022
    
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