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Trabecular Bone Anisotropy Characterization Using 1D Local Binary Patterns

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6474))

Abstract

This paper presents a new method to characterize the texture of gray level bone radiographic images. The technique is inspired from the Local Binary Pattern descriptor which has been classically applied on two dimensional (2D) images. Our algorithm is a derived solution for the 1D projected fields of the 2D images. The method requires a series of preprocessing of images. A clinical study is led on two populations of osteoporotic and control patients. The results show the ability of our technique to better discriminate the two populations than the classical LBP method. Moreover, they show that the structural organization of bone is more anisotropic for the osteoporotic cases than that of the control cases in accordance with the natural evolution of bone tissue linked to osteoporosis.

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Houam, L., Hafiane, A., Jennane, R., Boukrouche, A., Lespessailles, E. (2010). Trabecular Bone Anisotropy Characterization Using 1D Local Binary Patterns. In: Blanc-Talon, J., Bone, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2010. Lecture Notes in Computer Science, vol 6474. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17688-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-17688-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17687-6

  • Online ISBN: 978-3-642-17688-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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