
Root canal segmentation in cone-beam computed tomography
Author(s) -
Juliane Freitas Machado,
Paula Maciel Pires,
Thaís Maria Pires dos Santos,
Aline de Almeida Neves,
Ricardo Tadeu Lopes,
Maria Augusta Portella Guedes Visconti
Publication year - 2019
Publication title -
brazilian journal of oral sciences/brazilian journal of oral sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.125
H-Index - 11
eISSN - 1677-3225
pISSN - 1677-3217
DOI - 10.20396/bjos.v18i0.8657328
Subject(s) - cone beam computed tomography , segmentation , root canal , gold standard (test) , mathematics , computed tomography , artificial intelligence , tomography , nuclear medicine , computer science , medicine , computer vision , radiology , dentistry , statistics
Aim: The purpose of this study was to compare root canal volumes (RCVs) obtained by means of cone beam computed tomography (CBCT) to those obtained by micro-computed tomography (micro-CT) after applying different segmentation algorithms. Methods: Eighteen extracted human teeth with sound root canals were individually scanned in CBCT and micro-CT using specific acquisition parameters. Two different images segmentation strategies were applied to both acquisition methods (a visual and an automatic threshold). From each segmented tooth, the root canal volume was obtained. A paired t-test was used to identify differences between mean values resulted from the experimental groups and the gold standard. In addition, Pearson correlation coefficients and the agreement among the experimental groups with the gold standard were also calculated. The significance level adopted was 5%. Results: No statistical differences between the segmentation methods (visual and automatic) were observed for micro-CT acquired images. However, significant differences for the two segmentation methods tested were seen when CBCT acquired images were compared with the micro-CT automatic segmentation methods used. In general, an overestimation of the values in the visual method were observed while an underestimation was observed with the automatic segmentation algorithm. Conclusion: Cone beam computed tomography images acquired with parameters used in the present study resulted in low agreement with root canal volumes obtained with a micro-CT tomography gold standard method of RCV calculation.