Knowledge-based landmarking of cephalograms.
Orthodontists have defined a certain number of characteristic points, or landmarks, on X-ray images of the human skull which are used to study growth or as a diagnostic aid. This work presents the first step toward an automatic extraction of these points. They are defined with respect to particular lines which are retrieved first. The original image is preprocessed with a prefiltering operator (median filter) followed by an edge detector (Mero-Vassy operator). A knowledge-based line-following algorithm is subsequently applied, involving a production system with organized sets of rules and a simple interpreter. The a priori knowledge implemented in the algorithm must take into account the fact that the lines represent biological shapes and can vary considerably from one patient to the next. The performance of the algorithm is judged with the help of objective quality criteria. Determination of the exact shapes of the lines allows the computation of the positions of the landmarks.
D001185:Artificial Intelligence; D002508:Cephalometry / Q000379:methods*; D002648:Child; D005260:Female; D006257:Head / Q000000981:diagnostic imaging*; D006801:Humans; D008433:Mathematics; D009970:Orthodontics / Q000379:methods; D011856:Radiographic Image Enhancement; D013382:Subtraction Technique