Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33093
Trabecular Texture Analysis Using Fractal Metrics for Bone Fragility Assessment
Authors: Khaled Harrar, Rachid Jennane
Abstract:
The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an agematched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BMD.Keywords: Osteoporosis, fractal dimension, fractal signature, bone mineral density.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1108242
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2328References:
[1] R. Huang, Q. Rong, X. Han, Y. Li, “The effects of cod bone gelatin on trabecular microstructure and mechanical properties of cancellous bone,” Acta Mechanica Solida Sinica, vol. 28, no. 1, pp. 1–10, 2015.
[2] J. Montoya, M. Giner, C. Miranda, A.Vázquez, J. R. Caeiro, D. Guede, R. Pérez-Cano, “Microstructural trabecular bone from patients with osteoporotic hip fracture or osteoarthritis: Its relationship with bone mineral density and bone remodelling markers,” Maturitas, vol. 79, no. 3, pp. 299–305, 2014
[3] N. A. Valous, F. Mendoza, D. Sun, P. Allen, “Texture appearance characterization of pre-sliced pork ham images using fractal metrics: Fourier analysis dimension and lacunarity,” Food Research International, vol. 42, , pp. 353–362, 2009.
[4] G. Dougherty, G.M. Henebry, “Lacunarity analysis of spatial pattern in CT images of vertebral trabecular bone for assessing osteoporosis,” Medical Engineering & Physics, vol. 24, pp. 129–138, 2002.
[5] K. Harrar, L. Hamami, E. Lespessailles, R. Jennane, “Piecewise Whittle Estimator for Bone Radiograph Characterization,” Biomed. Signal Proces. vol. 8, no. 6, pp. 657–666, 2013.
[6] D. Sanchez-Molina, J. Velazquez-Ameijide, V. Quintana, C. Arregui- Dalmases, J.R. Crandall, D. Subit, J.R. Kerrigan, “Fractal dimension and mechanical properties of human cortical bone,” Medical Engineering & Physics, vol. 35, no. 5, pp. 576–582, 2013.
[7] L. Pothuaud, E. Lespessailles, R. Harba, R. Jennane, V. Royan, E. Eynard, C.L. Benhamou, “Fractal analysis of trabecular bone texture on radiographs: discriminant value in postmenopausal osteoporosis,” Osteoporosis International, vol. 8, pp. 618–625, 1998.
[8] C.L. Benhamou, E. Lespessailles, G. Jacquet, R. Harba, R. Jennane, T. Loussot, D. Tourliere, W. Ohley, “Fractal organization of trabecular bone images on calcaneus radiographs,” Journal of Bone and Mineral Research, vol. 9, pp. 1909–1918, 1994.
[9] N. Otsu, “A Threshold Selection Method from Gray-Level Histograms,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, no. 1, pp. 62-66, 1979.
[10] D. Marr, E.C. Hildreth, “Theory of edge detection,” Biological sciences, vol. 207, no. 1167, pp. 187–190, 1980.
[11] E.C. Hildreth, “The detection of intensity changes by computer and biological vision systems,” Computer Graphics and Image Processing, vol. 22, pp. 1–27, 1983.
[12] B.B. Mandelbrot, The fractal geometry of nature. Freeman. new York, 1983.
[13] J. Li, Q. Du, C. Sun, “An improved box-counting method for image fractal dimension estimation,” Pattern Recognition, vol. 42, no. 11, pp. 2460-2469, 2009.
[14] K.J. Falkoner, Techniques in Fractal Geometry. John Wiley & Sons, Ltd. Chichester, 1997.
[15] A.P. Pentland, “Fractal-based description of natural scenes,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, no. 6, pp. 661–74, 1984.
[16] J. Feder, 1988. Fractals Plenum. Press, New York.
[17] J.A. Lynch, D.J. Hawkes, J.C. Buckland-Wright, “Analysis of texture in macroradiographs of osteoarthritic knees using the fractal signature,” Physics in Medecine and Biology, vol. 36, pp. 709-722, 1996.
[18] S. Majumdar, R. S. Weinstein, R. R. Prasad, H. K. Genant, “The fractal dimension of trabecular bone: a measure of trabecular structure,” Calcified Tissue International, vol. 52, no. 168, 1993.
[19] E.A. Messent, J.C. Buckland-Wright, G.M. Blake, “Fractal analysis of trabecular bone in knee osteoarthritis (OA) is a more sensitive marker of disease status than bone mineral density (BMD),” Calcif Tissue Int. vol. 76, no. 6, pp.419-25, 2005.
[20] J.C. Buckland-Wright, J.A. Lynch, D.G. Macfarlane, “Fractal signature analysis measures cancellous bone organization in macroradiographs of patients with knee osteoarthritis,” Ann Rheum Dis, vol. 55, pp. 749–755, 1996.
[21] E. Lespessailles, C. Chappard, N. Bonnet, C.L. Benhamou, “Techniques for evaluating bone microarchitecture,” Joint Bone Spine, vol. 73, pp. 254–261, 2006.
[22] W.G.M. Geraets, J.G.C. Verheij, P.F. van der Stelt, K. Horner, C. Lindh, K. Nicopoulou-Karayianni, R. Jacobs, E.J. Harrison, J.E. Adams, H. Devlin, “Prediction of bone mineral density with dental radiographs,” Bone, vol. 40, pp. 1217–1221, 2007.
[23] M.E. Kersh, P.K. Zysset, D.H. Pahr, U. Wolfram, D. Larsson, M.G. Pandy, Measurement of structural anisotropy in fe W. D. Doyle, “Magnetization reversal in films with biaxial anisotropy,” in 1987 Proc. INTERMAG Conf., pp. 2.2-1–2.2-6.
[24] K. Harrar, R. Jennane, “Quantification of Trabecular Bone Porosity on X-Ray Images”, 4th International Conference on Industrial and Intelligent Information (ICIII 2015), 18-19 May 2015, Roma, Italy.