title: Automated 2-D cephalometric analysis on X-ray images by a model-based approach.
abstract: Craniofacial landmark localization and anatomical structure tracing on cephalograms are two important ways to obtain the cephalometric analysis. In order to computerize them in parallel, a model-based approach is proposed to locate 262 craniofacial feature points, including 90 landmarks and 172 auxiliary points. In model training, 12 landmarks are selected as reference points and used to divide every training shape to 10 regions according to the anatomical knowledge; principle components analysis is employed to characterize the region shape variations and the statistical grey profile of every feature point. Locating feature points on an input image is a two-stage procedure. First, we identify the reference landmarks by image processing and pattern matching techniques, so that the shape partition is performed on the input image. Then, for each region, its feature points are located by a modified active shape model. All craniofacial anatomical structures can be traced out by connecting the located points with subdivision curves according to the prior knowledge. Users are permitted to modify the results interactively in many different ways. Experimental results show the advantage and reliability of the proposed method.
authors.affiliation: School of Electronics Engineering and Computer Science, Peking University, Beijing, China. yue@graphics.pku.edu.cn
authors.forename: Weining
authors.initials: W
authors.lastname: Yue
authors.forename: Dali
authors.initials: D
authors.lastname: Yin
authors.forename: Chengjun
authors.initials: C
authors.lastname: Li
authors.forename: Guoping
authors.initials: G
authors.lastname: Wang
authors.forename: Tianmin
authors.initials: T
authors.lastname: Xu
mesh_terms: D000293:Adolescent; D000465:Algorithms; D001185:Artificial Intelligence; D002508:Cephalometry / Q000379:methods*; D002648:Child; D003198:Computer Simulation; D005260:Female; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012886:Skull / Q000000981:diagnostic imaging*