Abstract
3D CBCT imaging plays an important role in diagnosis and treatment planning in orthodontics. The 3D tooth segmentation and reconstruction are a vital precondition. In the article, we propose two algorithms: (1). a novel image segmentation algorithm with two thresholds to separate teeth from soft tissue; (2). a local region-growing algorithm for 3D tooth extraction is created by using the local maximum gray-scale value taken as the seed point. The resulting object is defined as a single connected component containing both the seed point and voxels with gray-values lying between the local seed point and the threshold. The 3D tooth is reconstructed from the stack of the segmented image slices. Then we use VC++, OpenGL, VTK and ITK to implement the algorithms, automatic rearrangement of teeth, and 3D virtual simulation of treatment planning. It has been shown that the algorithms are robust and effective and the 3D teeth visualization software can fit into dentist’s diagnosis and treatment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alcañiz, M., Chinesta, F., Monserrat, C., Grau, V., Ramón, A.: An Advanced System for the Simulation and Planning of Orthodontic Treatments. In: Höhne, K.H., Kikinis, R. (eds.) VBC 1996. LNCS, vol. 1131, pp. 511–520. Springer, Heidelberg (1996)
Leifert, M., Leifert, M., Efstratiadis, S., Cangialosi, T.: Comparison of Space Analysis Evaluations with Digital Models and Plaster Dental Casts. Am. J. Orthod. Dentofacial Orthop. 7, 136–152 (2009)
Visualization Toolkit (VTK) Information, http://www.vtk.org
Avila, L.S., Barré, S., Blue, R., Cole, D.: The VTK User Guide Updated for Version 5, Colombia, Kitware (2006)
Insight Toolkit (ITK) Information, http://www.itk.org
Hilgers, M.L., Scarfe, W.C., Scheetz, J.P., Farman, A.G.: Accuracy of Linear Temporomandibular Joint Measurements with Cone Beam Computed Tomography and Digital Cephalometric Radiography. Am. J. Orthod Dentofacial Orthop. 128, 803–811 (2005)
Pasini, A., Casali, F., Biaconi, D.: A New Cone-Beam Computed Tomography System for Dental Applications with Innovative 3D Software. International Journal of Computer Assisted Radiology and Surgery 1, 265–273 (2006)
DICOM Information, http://medical.nema.org
Otsu, N.: A Threshold Selection Method from Gray-Level Histogram. IEEE Trans. Syst. Man Cybern. 9, 62–66 (1979)
Hojjatoleslami, S.A., Kittler, J.: Region Growing: A New Approach. IEEE Transactions on Image Processing 7, 1079–1084 (1998)
Li, G., Wan, Y.C.: Adaptive Seeded Region Growing for Image Segmentation Based on Edge Detection, Texture Extraction and Cloud Model. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds.) ICICA 2010. LNCS, vol. 6377, pp. 285–292. Springer, Heidelberg (2010)
Alazab, M., Islam, M., Venkatraman, S.: Towards automatic image segmentation using optimised region growing technique. In: Nicholson, A., Li, X. (eds.) AI 2009. LNCS, vol. 5866, pp. 131–139. Springer, Heidelberg (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, W. (2011). Algorithms of 3D Segmentation and Reconstruction Based on Teeth CBCT Images. In: Ma, M. (eds) Communication Systems and Information Technology. Lecture Notes in Electrical Engineering, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21762-3_93
Download citation
DOI: https://doi.org/10.1007/978-3-642-21762-3_93
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21761-6
Online ISBN: 978-3-642-21762-3
eBook Packages: EngineeringEngineering (R0)