Locating large-scale craniofacial feature points on X-ray images for automated cephalometric analysis

With the objective of tracing out all craniofacial structures in parallel with landmarking on X-ray images in cephalometry for the first time, a novel approach is proposed to locate 262 feature points composed of 90 landmarks and 172 auxiliary points. Twelve landmarks are identified by classical image processing techniques and a pattern matching algorithm, and then are used to divide the craniofacial shape to ten independent regions according to the anatomical knowledge. For each region, principal component analysis is employed to statistically characterize its shape and the gray profile of every feature point in the training, and a modified active shape model is proposed for localization. We conclude with experiment results and some discussion.