Abstract
This paper presents a method for segmenting the inferior maxillary bone in CT images and a technique to automatically classify bone tissue without requiring a training stage. These methods are used to measure the mean density of seven main anatomical zones of the mandible, making the difference between cortical and cancellous bone. The results lead to determine the normal density values in each region of the inferior maxillary bone and help to evaluate the success of the bone regeneration process. The proposed method was validated on ten axial slices from different zones of a patient mandible, by comparing automatic classification results with those obtained by expert manual classification. A 4% mean difference was found between percentages of bone tissue types, and the mean difference between mean density values was of 88 HU. Once the method was validated, it was applied to measure density in the seven anatomical zones of the inferior maxillary bone.
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References
Rickey, F.A., Elmore, D., Hillegonds, D., Badylak, S., Record, R., Simmons-Byrd, A.: Re-generation of tissue about an animal-based scaffold: AMS studies of the fate of the scaffold. Nucl. Instrum Meth. B 172(1-4), 904–909 (2000)
Tognola, G., Parazzini, M., Pedretti, G., Ravazzani, P., Svelto, C., Norgia, M., Grandori, F.: Three- Dimensional Reconstruction and Image Processing in Mandibular Distraction Planning. IEEE T. Instrum. Meas. 55(6), 1959–1964 (2006)
Barandiaran, I., Macía, I., Berckmann, E., Wald, D., Dupillier, M.P., Paloc, C., Graña, M.: An Automatic Segmentation and Reconstruction of Mandibular Structures from CT-Data. In: Corchado, E., Yin, H. (eds.) IDEAL 2009. LNCS, vol. 5788, pp. 649–655. Springer, Heidelberg (2009)
Krsek, P., Spanel, M., Krupa, P., Marek, I., Cernochov, P.: Teeth and Jaw 3D Reconstrucion in Stomatology. In: Proceedings of the International Conference on Medical information Visualisation - Biomedical Visualisation, Zurich, Switzerland, pp. 23–28. IEEE Computer Society, Los Alamitos (2007)
Futterling, F., Klein, R., Straber, W., Weber, H.: Automated Finite Element Modeling of a Human Mandible with Dental Implants. In: 6th International Conference in Central Europe on Computer Graphics and Visualization (1998)
Rueda, S., Gil, J.A., Pichery, R., Alcañiz, M.: Automatic Segmentation of Jaw Tissues in CT Using Active Appearance Models and Semi-automatic Landmarking. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 167–174. Springer, Heidelberg (2006)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice Hall, Englewood Cliffs (2008)
Lorenz, C., von Berg, J.: Fast automated object detection by recursive casting of search rays. In: CARS 2005: Computer Assisted Radiology and Surgery, vol. 1281, pp. 230–235 (2005)
Dunn, J.C.: A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters. Cybernetics and Systems 3(3), 32–57 (1976)
ImageJ (2009), http://rsbweb.nih.gov/ij (Cited November 30)
Kitware, Inc.: The Visualization Toolkit (2009), http://www.vtk.org (Cited July 30)
Creatis LRMN (2009) CreaTools Available from, http://www.creatis.insa-lyon.fr/creatools (Cited July 30)
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Moreno, S. et al. (2010). Inferior Maxillary Bone Tissue Classification in 3D CT Images. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15907-7_18
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DOI: https://doi.org/10.1007/978-3-642-15907-7_18
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