ArticleScientific data2024
A multimodal dental dataset facilitating machine learning research and clinic services.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Artificial Intelligence-Driven Segmentation of Three Oral Diseases: Enabling Precision Diagnosis and Decision Support.International dental journal · 2026Article
- A benchmark multimodal oro-dental dataset for large vision-language models.Scientific data · 2026Article
- Adults' dental cone beam computed tomography images dataset for detecting and classifying missing teeth.Scientific data · 2026Article
- Dental Odontogenic Lesion CBCT and Histopathology Integrated Dataset for Benchmarking Deep Learning Algorithms.Scientific data · 2026Article
- BRAR-anchored multimodal dataset of panoramic radiographs for periodontal bone resorption grading.Scientific data · 2025Article
- [A sparse-view cone-beam CT reconstruction algorithm based on bidirectional flow field- guided projection completion].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025Article
- A multimodal dental dataset facilitating machine learning research and clinic services.Scientific data · 2024Article
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Authors and funding
11 authors.
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Abstract
Oral diseases affect nearly 3.5 billion people, and medical resources are limited, which makes access to oral health services nontrivial. Imaging-based machine learning technology is one of the most promising technologies to improve oral medical services and reduce patient costs. The development of machine learning technology requires publicly accessible datasets. However, previous public dental datasets have several limitations: a small volume of computed tomography (CT) images, a lack of multimodal data, and a lack of complexity and diversity of data. These issues are detrimental to the development of the field of dentistry. Thus, to solve these problems, this paper introduces a new dental dataset that contains 169 patients, three commonly used dental image modalities, and images of various health conditions of the oral cavity. The proposed dataset has good potential to facilitate research on oral medical services, such as reconstructing the 3D structure of assisting clinicians in diagnosis and treatment, image translation, and image segmentation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.