Model-Based Orthodontic Assessments for Dental Panoramic Radiographs

Chia Hsiang Wu, Wan Hua Tsai, Ying Hui Chen, Jia Kuang Liu, Yung Nien Sun

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


For better treatment outcomes, dentists usually use a set of parameters for orthodontic evaluation. In this study, a new method is proposed to assist dentists in obtaining reliable assessment of these parameters. The proposed method is based on dental panoramic radiographs and can be divided into four stages: image preprocessing, model training, tooth segmentation, and assessment of orthodontic parameters. The image is first normalized and enhanced. Then, the model training stage consists of shape and image model training, energy function training, and weight training. Next, we automatically segment the tooth contours in an energy-minimized manner. Finally, the automatic assessment of orthodontic parameters is carried out. The experimental results show that the average of absolute distance, the Dice similarity coefficient, and the average qualitative score ranged between 4.17 and 6.03, 0.87 and 0.90, as well as 2.58 and 3.12, respectively. The orthodontic assessment also is close to the evaluation of orthodontists. It has been shown that the proposed method can obtain accurate and consistent measurement in helping dentists to obtain an objective treatment evaluation.

Original languageEnglish
Pages (from-to)545-551
Number of pages7
JournalIEEE Journal of Biomedical and Health Informatics
Issue number2
Publication statusPublished - 2018 Mar

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management


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