Abstract
Osteoporosis is due to the following two phenomena: a reduction bone mass and a degradation of the microarchitecture of bone tissue. In this paper, we propose a method for extracting morphological information enabling the description of bone structure from radiological images of the calcaneus. Our main contribution relies on the fact that we provide bone descriptors close to classical 3D-morphological bone parameters. The first step of the proposed method consists in extracting the grey-scale skeleton of the microstructures contained in the underlying images. After an appropriate processing, the resulting skeleton provides discriminant features between osteoporotic patients and control patients. Statistical tests corroborate this discrimination property.
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References
Consensus development Conference: diagnosis, prophylaxis, and treatment of osteoporosis. Amer. J. Med. 94(6), 646–650 (1993)
Goldstein, S.A.: The mechanical properties of trabecular bone: Dependence on anatomic location and function. J. Biomech. 20, 1055–1061 (1987)
Majumdar, S., Newitt, D., Jergas, M., Gies, A., et al.: Evaluation of technical factors affecting the quantification of trabecular bone structure using magnetic resonance imaging. Bone 17, 417–430 (1995)
Paquet, V., Battut, P., Blanc, H.V., Ferrand, D.: On the use of grey run lenth matrices in trabecular bone analysis. In: Proc. of the Conf. on the Image Proc. and its Applic. July 4-6, pp. 445–449 (1995)
Lundahl, T., Ohley, W.J., Kay, S.M., Siffert, R.: Fractional Brownian motion: a maximum likelihood estimator and its application to image texture. IEEE Trans. Med. Imag. MI-5(3), 152–161 (1986)
Benhamou, C.L., Harba, R., Lespessailles, E., Jacquet, E., Toulière, D., Jennane, R.: Fractal organisation of trabecular bone images on calcaneus radiographs. J. Bone Mineral Res. 9, 1909–1918 (1994)
Southard, T.E., Southard, K.A.: Detection of simulated osteoporosis in maxillae using radiographic texture analysis. IEEE Trans. on Biomed. Eng. 43(2), 123–132 (1996)
Gregory, J.S., Junold, R.M., Undrill, P.E., Aspden, R.M.: Analysis of trabecular bone structure using Fourier transforms and neural networks. IEEE Trans. on Inf. Tech. in Biomed. 3(4), 289–294 (1999)
Geraets, W.G.M.: Computer-aided analysis of the radiographic trabecular pattern, Ph. D. Thesis, Netherlands
Arcelli, C., Ramella, G.: Finding grey skeletons by iterated pixel removal. Image and Vision Computing 13(3), 159–267 (1995)
Chen, S., Shih, F.Y.: Skeletonization for fuzzy degraded character images. IEEE Trans. on Image Proc. 5(10), 1481–1485 (1996)
Mersal, S.S., Darwish, A.M.: A new parallel thinning algorithm for gray scale images. In: IEEE Nonlinear Signal and Image Proc. Conf. Antalya, Turkey (June 1999)
Sevestre-Ghalila, S., Benazza-Benyahia, A., Cherif, H., Souid, W.: Texture analysis for osteoporosis detection with morphological tools. In: Sonka, M., Hanson, K.M. (eds.) Medical Imaging 2001, SPIE Conf., San Diego, California, USA, February 17-23, vol. 4322, pp. 1534–1541 (2001)
Steger, C.: Unbiased extraction of curvilinear structures from 2D and 3D images, PhD Thesis, Technical University of Munchen (1998)
Banerji, P., Kabra, S.G.: The trabecular pattern of calcaneus as an index of osteoporosis. Journal British Editorial Society of Bonne and joint Surgery 65-B(2), 195–198 (1983)
Koller, T., Grieg, C., Szekély, G., Dettwiler, D.: Multiscale detection of curvilinear structures in 2D and 3D image data. In: Proc. of the Fifth Internat. Conf. on Computer Vision, pp. 864–869 (1995)
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Sevestre-Ghalila, S., Benazza-Benyahia, A., Ricordeau, A., Mellouli, N., Chappard, C., Benhamou, C.L. (2004). Texture Image Analysis for Osteoporosis Detection with Morphological Tools. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_11
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DOI: https://doi.org/10.1007/978-3-540-30135-6_11
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