Quantitative cephalometric analysis is the most widely used clinical and research tool in modern orthodontics. Accurate localization of cephalometric landmarks enables the quantification and classification of anatomical abnormalities, however, the traditional manual way of marking these landmarks is a very tedious job. Endeavours have constantly been made to develop automated cephalometric landmark detection systems but they are inadequate for orthodontic applications. The fundamental reason for this is that the amount of publicly available datasets as well as the images provided for training in these datasets are insufficient for an AI model to perform well. To facilitate the development of robust AI solutions for morphometric analysis, we organise the CEPHA29 Automatic Cephalometric Landmark Detection Challenge in conjunction with IEEE International Symposium on Biomedical Imaging (ISBI 2023). In this context, we provide the largest known publicly available dataset, consisting of 1000 cephalometric X-ray images. We hope that our challenge will not only derive forward research and innovation in automatic cephalometric landmark identification but will also signal the beginning of a new era in the discipline.

翻译：定量头影测量分析是现代正畸学中应用最广泛的临床和研究工具。精确的头影测量标志点定位能够量化并分类解剖异常，然而传统的人工标注方式极其繁琐。尽管开发自动头影测量标志点检测系统的努力从未间断，但这些系统仍不足以满足正畸应用需求。其根本原因在于，公开可用的数据集数量以及这些数据集中提供的训练图像不足以支撑人工智能模型取得优异表现。为促进形态测量分析的稳健人工智能解决方案发展，我们与IEEE国际生物医学成像研讨会（ISBI 2023）联合组织了CEPHA29自动头影测量标志点检测挑战赛。为此，我们提供了目前已知规模最大的公开数据集，包含1000张头影测量X光图像。我们期望此次挑战赛不仅能推动自动头影测量标志点识别的研发与创新，更将标志着该学科迈入新时代的开端。