A new methodology for automatic detection of reference points in 3D cephalometry: A pilot study (original) (raw)

Automatic Cephalometric Analysis

Angle Orthodontist, 2008

Objective: To describe the techniques used for automatic landmarking of cephalograms, highlighting the strengths and weaknesses of each one and reviewing the percentage of success in locating each cephalometric point. Materials and Methods: The literature survey was performed by searching the Medline, the Institute of Electrical and Electronics Engineers, and the ISI Web of Science Citation Index databases. The survey covered the period from January 1966 to August 2006. Abstracts that appeared to fulfill the initial selection criteria were selected by consensus. The original articles were then retrieved. Their references were also hand-searched for possible missing articles. The search strategy resulted in 118 articles of which eight met the inclusion criteria. Many articles were rejected for different reasons; among these, the most frequent was that results of accuracy for automatic landmark recognition were presented as a percentage of success. Results: A marked difference in results was found between the included studies consisting of heterogeneity in the performance of techniques to detect the same landmark. All in all, hybrid approaches detected cephalometric points with a higher accuracy in contrast to the results for the same points obtained by the model-based, image filtering plus knowledge-based landmark search and ''soft-computing'' approaches. Conclusions: The systems described in the literature are not accurate enough to allow their use for clinical purposes. Errors in landmark detection were greater than those expected with manual tracing and, therefore, the scientific evidence supporting the use of automatic landmarking is low.

Accuracy of computerized automatic identification of cephalometric landmarks

American Journal of Orthodontics and Dentofacial Orthopedics, 2000

Computerized cephalometric analysis can include both landmark identification and determination of linear or angular measurements. Although its use is time saving compared with a manual method, the accuracy of automatic landmark identification remains unclear. The purpose of this study was to evaluate the accuracy of a computerized automatic landmark identification system that used an edge-based technique. The technique divides the scanned cephalogram into 8 rectangular subimage regions. After the resolution of these subimages is reduced, the edges are detected and the landmarks are located automatically. Thirteen landmarks were selected for assessment on a set of 10 test cephalograms. The results showed that the errors between manual and computerized identification for landmarks were not significantly different (P > .05) for 5 of 13 landmarks: sella, nasion, porion, orbitale, and gnathion. These results suggest that the accuracy of computerized automatic identification is acceptable for certain landmarks only. Further studies to improve the accuracy of computerized automated landmark identification are needed.