Automatic image slice marking propagation on segmentation of dental CBCT

Agus Zainal Arifin*, Evan Tanuwijaya, Baskoro Nugroho, Arif Mudi Priyatno, Rarasmaya Indraswari, Eha Renwi Astuti, Dini Adni Navastara

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Cone Beam Computed Tomography (CBCT) is a radiographic technique that has been commonly used to help doctors provide more detailed information for further examination. Teeth segmentation on CBCT image has many challenges such as low contrast, blurred teeth boundary and irregular contour of the teeth. In addition, because the CBCT produces a lot of slices, in which the neighboring slices have related information, the semi-automatic image segmentation method, that needs manual marking from the user, becomes exhaustive and inefficient. In this research, we propose an automatic image slice marking propagation on segmentation of dental CBCT. The segmentation result of the first slice will be propagated as the marker for the segmentation of the next slices. The experimental results show that the proposed method is successful in segmenting the teeth on CBCT images with the value of Misclassification Error (ME) and Relative Foreground Area Error (RAE) of 0.112 and 0.478, respectively.

Original languageEnglish
Pages (from-to)3218-3225
Number of pages8
JournalTelkomnika (Telecommunication Computing Electronics and Control)
Issue number6
Publication statusPublished - Dec 2019


  • Automatic segmentation
  • Dental CBCT
  • Hierarchical clustering
  • Mean-shift
  • Morphology


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