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，合称FD）的自动化检测研发的综合性数据集，整合了241名年龄介于9至55岁患者的口内照片与对应锥形束计算机断层扫描（CBCT）影像。该数据集包含1800份针对口内照片的标注边界框，其中锥形束计算机断层扫描（CBCT）作为评估骨缺损的首选成像模态。它可为跨学科牙科研究提供支撑，助力开发用于非侵入式FD筛查的深度学习模型，并提供一种可降低辐射暴露的替代评估方案。FDTooth可作为推动牙科诊断发展、专业人员培训以及探索牙科与颌面成像其他应用场景的宝贵资源。

搜集汇总

背景与挑战

背景概述

FDTooth是一个专注于牙槽骨开窗和开裂（FD）检测的牙科影像数据集，包含241名9-55岁患者的口内照片和对应锥形束CT（CBCT）图像，共标注了2892颗前牙的FD状态。该数据集支持深度学习模型开发，用于非侵入性FD筛查，并提供了患者人口统计学信息和高质量标注，适用于牙科AI研究、教育及临床诊断应用。