Shape of the dental root canal is highly patient specific. Automated identification
methods of the
medial line of dental root canals and the reproduction of their 3D shape can be beneficial
planning endodontic interventions as severely curved root canals or multi-rooted teeth
treatment challenges. Accurate shape information of the root canals may also be used
manufacturers of endodontic instruments in order to make more efficient clinical tools.
Novel image processing procedures dedicated to the automated detection of the medial
axis of the
root canal from dental micro-CT and cone-beam CT records are developed. For micro-CT,
model of the root canal is built up from several hundred parallel cross sections,
enhancement, histogram based fuzzy c-means clustering, center point detection in the
slice, three dimensional inner surface reconstruction, and potential field driven
extraction in three dimensions. Cone-beam CT records are processed with image enhancement
and fuzzy chain based regional segmentation, followed by the reconstruction of the
surface and detecting its skeleton via a mesh contraction algorithm.
The proposed medial line identification and root canal detection algorithms are validated
data sets. 25 micro-CT and 36 cone-beam-CT records are used in the validation procedure.
overall success rate of the automatic dental root canal identification was about 92%
procedures. The algorithms proved to be accurate enough for endodontic therapy planning.
Accurate medial line identification and shape detection algorithms of dental root
canal have been
developed. Different procedures are defined for micro-CT and cone-beam CT records.
automated execution of the subsequent processing steps allows easy application of
the algorithms in
the dental care. The output data of the image processing procedures is suitable for
modeling of the central line. The proposed methods can help automate the preparation
and design of
several kinds of endodontic interventions.