Model-based segmentation of reconstructed dental x-ray volumes

Kari Antila, Mikko Lilja, Martti Kalke, Jyrki Lötjönen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)

Abstract

Modern reconstruction algorithms allow volumetric imaging with conventional 2D dental X-ray systems. Volumetric images are useful in dental implantology, where the correct identification of key structures such as the edges of the mandible and the mandibular nerve is critical. This paper presents a segmentation method capable of extracting the mandible. The segmentation is based on a statistical model which was first transformed affinely and finally deformed non-rigidly to the object. The method was tested on three volumes with good results: mean distances between the deformed and manually segmented reference surfaces were 0.26, 0.34 and 0.50 mm. Applications of the method include the extraction of slices orthogonal to the mandibular bone centerline and local, anatomy based image enhancement.
Original languageEnglish
Title of host publication2006 International Conference on Image Processing
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages1933 -1936
ISBN (Print)1-4244-0481-9
DOIs
Publication statusPublished - 2006
MoE publication typeA4 Article in a conference publication

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Keywords

  • image segmentation
  • biomedical image
  • processing
  • X-ray imaging

Cite this

Antila, K., Lilja, M., Kalke, M., & Lötjönen, J. (2006). Model-based segmentation of reconstructed dental x-ray volumes. In 2006 International Conference on Image Processing (pp. 1933 -1936). IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/ICIP.2006.312792