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Three-Dimensional Tooth Segmentation by Integrating Multiple Ray-Sum Images From CBCT Data

[+] Author Affiliations
Sandro Barone, Alessandro Paoli, Armando V. Razionale

University of Pisa, Pisa, Italy

Paper No. DETC2015-47197, pp. V01AT02A050; 8 pages
doi:10.1115/DETC2015-47197
From:
  • ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1A: 35th Computers and Information in Engineering Conference
  • Boston, Massachusetts, USA, August 2–5, 2015
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5704-5
  • Copyright © 2015 by ASME

abstract

The reconstruction of tooth anatomies is of utmost importance when dental implant surgeries and/or orthodontic corrections must be planned. In the last few years, cone beam CT (CBCT) has gained popularity in dentistry for 3D imaging of jawbones and teeth. However, within CBCT data sets, each tooth is defined by a region, which cannot be easily separated from surrounding tissues (i.e., bone tissue) by only considering pixel’s grey-intensity values. For this reason, some enhancement is usually necessary in order to properly segment tooth geometries.

In this paper, a semi-automatic approach to reconstruct individual 3D tooth anatomies by processing CBCT-scan data is presented. The methodology is based on the creation of a minimal number of 2D “local ray-sum” images by adding the absorption values of adjacent voxels along the most significant views for each tooth. The knowledge of the specific anatomical patient morphology drives the selection of these significant projection directions. The reconstructed “ray-sum” images greatly enhance the clearness of the root contours, which can then be interactively traced by dentists. A set of meaningful 2D tooth contours is consequently obtained and used to automatically extract a cubic spline curve for each transverse slice, thus approximating the overall 3D tooth profile.

The effectiveness of the methodology has been evaluated by comparing the results obtained for the reconstruction of anterior teeth with those obtained by using classical segmentation tools provided within commercial software.

Copyright © 2015 by ASME

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