Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin, 541004, China.
Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, China.
Sci Data. 2024 Nov 27;11(1):1291. doi: 10.1038/s41597-024-04130-1.
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.
口腔疾病影响了近 35 亿人，而医疗资源有限，这使得获得口腔健康服务变得不那么容易。基于影像的机器学习技术是改善口腔医疗服务和降低患者成本的最有前途的技术之一。机器学习技术的发展需要可公开访问的数据集。然而，以前的公共牙科数据集存在几个限制：计算机断层扫描 (CT) 图像的数量较少，缺乏多模态数据，以及数据的复杂性和多样性不足。这些问题不利于牙科领域的发展。因此，为了解决这些问题，本文介绍了一个新的牙科数据集，其中包含 169 名患者、三种常用的牙科图像模态以及口腔各种健康状况的图像。该数据集具有很好的潜力，可以促进口腔医疗服务的研究，例如重建 3D 结构以辅助临床医生进行诊断和治疗、图像翻译和图像分割。
