Abstract
We propose a CT image segmentation method using structural analysis. The aim of our research is to decompose assembled fossil of skeletons and crania into fragments in the area of fossil reconstruction. One challenge specific to this type of segmentation procedure is the separation of fragments where their gaps are not necessarily clear. We previously proposed a method of segmenting CT images using structural analysis. This technique is based on the assumption that the interference area (joint) between components (bones) is structurally weak. We compute strain, which tends to be large in structurally weak areas and segment the image in the region of high strain. With this approach, there is a need to specify boundary conditions for the structural analysis, namely, loading conditions (loading forces and their positions) and locations of fixed boundaries. In our previous work, we proposed a method of optimizing loading forces given loading positions and fixed boundary positions. In this study, we propose a method to find both of those positions to automate the segmentation procedure. Some segmentation results generated by our prototype software demonstrate applicability of the proposed method.
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
References
Adams R, Bischof L (1994) Seeded region growing. IEEE Trans Pattern Anal Mach Intell 16:641–647
Bendsoe M, Kikuchi N (1988) Generating optimal topologies in structural design using a homogenization method. Comput Methods Appl Mech Eng 71:197–224
Boykov Y, Funka-Lea G (2006) Graph cuts and efficient N-D image segmentation. Int J Comput Vis 70:109–131
Grau V, Mewes A, Alcaniz M, Kikinis R, Warfield S (2004) Improved watershed transform for medical image segmentation using prior information. IEEE Trans Med Imaging 23:447–458
Hahn H, Wenzel M, Konrad-Verse O, Peitgen H (2006) A minimally-interactive watershed algorithm designed for efficient CTA bone removal. Comput Vis Approaches Med Image Anal 178–189
Hishida H, Suzuki H, Michikawa T, Ohtake Y, Oota S (2012) CT image segmentation using FEM with optimized boundary condition. PLoS One 7:2–1
Joliot M, Mazoyer B (1993) Three-dimensional segmentation and interpolation of magnetic resonance brain images. IEEE Trans Med Imaging 12:269–277
Kass M, Witkin A, Terzopoulos D (1988) Snakes: active contour models. Int J Comput Vis 1:321–331
Mat-Isa N, Mashor M, Othman N (2005) Seeded region growing features extraction algorithm; its potential use in improving screening for cervical cancer. Int J Comput Internet Manag 13:61–70, ISSN No: 0858-7027
Pardo X, Carreira M, Mosquera A, Cabello D (2001) A snake for CT image segmentation integrating region and edge information. Image Vis Comput 19:461–475
Rao SS (2005) The finite element method in engineering, 4th edn. Elsevier Butterworth Heinemann, Oxford. ISBN 978-0-7506-7828-5
Sebastian T, Tek H, Crisco J, Kimia B (2003) Segmentation of carpal bones from CT images using skeletally coupled deformable models. Med Image Anal 7:21–45
Vincent L, Soille P (1991) Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans Pattern Anal Mach Intell 13(6):583–598
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Japan
About this chapter
Cite this chapter
Suzuki, H. et al. (2014). CT Image Segmentation for Bone Structures Using Image-Based FEM. In: Akazawa, T., Ogihara, N., C Tanabe, H., Terashima, H. (eds) Dynamics of Learning in Neanderthals and Modern Humans Volume 2. Replacement of Neanderthals by Modern Humans Series. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54553-8_20
Download citation
DOI: https://doi.org/10.1007/978-4-431-54553-8_20
Published:
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-54552-1
Online ISBN: 978-4-431-54553-8
eBook Packages: Humanities, Social Sciences and LawSocial Sciences (R0)