Tufts Dental Database: A Multimodal Panoramic X-Ray Dataset for Benchmarking Diagnostic Systems

Abstract

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. The Tufts Dental Database, a new X-ray panoramic radiography image dataset, has been presented in this paper. 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.

OdontoAI: A human-in-the-loop labeled data set and an online platform to boost research on dental panoramic radiographs

“…In this work, we constructed a large-size labeled data set of dental panoramic radiographs: the OdontoAI Open Panoramic Radiographs (O 2 PR) data set. The O 2 PR comprises 4000 images, in which the teeth were segmented and numbered, and is four times larger than the previously most extensive data set on the matter available in the literature (Panetta et al, 2021). The labels of 2,000 radiographs of the O 2 PR data set are publicly available, while the labels of the remaining others remain private for solution assessments at our online platform, the OdontoAI platform.…”

Caries Detection from Dental Images using Novel Maximum Directional Pattern (MDP) and Deep Learning

“…Big data helps in the gathering of knowledge from various resources that helps in a significant improvement of the accuracy and speed during decision making. Most of the models used were based on neural networks in identifying Cephalometric landmarks, assessing the cervical vertebrae growth and maturation, treatment planning, prediction of orthognathic surgeries, dental images, forecasting the facial appeal and post-orthognathic surgery facial shape [3,4]. More research should be included on incorporating big data to progress learning algorithms and decision-making systems with maximum accuracy.…”

A High-Accuracy Detection System: Based on Transfer Learning for Apical Lesions on Periapical Radiograph

“…X-rays have been used in medical images since 1896, and they also help doctors determine whether a patient is healthy. X-rays are widely used in dental treatments [ 1 ], such as periapical radiographs (PA), bitewing radiographs (BW), and panoramic radiographs (PANO). The PA film is important in routine dental X-ray examinations because it requires lower radiation dose exposure and could identify periapical pathology efficiently.…”