FDTooth: Intraoral Photographs and Cone-Beam Computed Tomography Images for Fenestration and Dehiscence Detection

FDTooth is a comprehensive dataset designed for the automated detection of
fenestration and dehiscence (FD) in anterior teeth, combining intraoral
photographs and corresponding cone-beam computed tomography (CBCT) images from
241 patients aged 9 to 55 years. The dataset includes 1,800 annotated bounding
boxes for intraoral photographs, with cone-beam computed tomography (CBCT)
serving as the imaging modality of choice for assessing bone defects. It
supports interdisciplinary dental research by enabling the development of deep
learning models for non-invasive FD screening, providing an alternative
assessment method that reduces radiation exposure. FDTooth serves as a
valuable resource for advancing dental diagnostics, training professionals,
and exploring other applications in dental and maxillofacial imaging.

FDTooth是一款专为前牙骨开窗（fenestration）与骨开裂（dehiscence，下称FD）的自动检测任务构建的综合数据集，其纳入了241名年龄介于9至55岁患者的口内照片与对应的锥形束计算机断层扫描（cone-beam computed tomography，下称CBCT）影像。该数据集包含1800个针对口内照片的标注边界框，其中CBCT作为评估骨缺损的首选成像模态。本数据集可支撑跨学科牙科研究，助力开发用于无创FD筛查的深度学习模型，提供一种可降低辐射暴露的替代评估手段。FDTooth作为一项宝贵的研究资源，能够推动牙科诊断技术的进步、辅助专业人员培训，并拓展牙科与颌面成像领域的其他应用场景。