  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.
