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Multifractal analysis by the large deviation spectrum to detect osteoporosis

Abstract : This work is based on the use of the theory of large deviations to calculate the grain multifractal spectrum and classify bone micro architecture texture, to do this the multifractal spectrum mode is used, it gives the fractal dimension of the predominant fractal set to detect osteoporosis. In fact, one of the most relevant parameters to differentiate between pathological and normal cases in the trabecular ROI texture is the distance of separation between trabeculae in bone micro architecture. The method we propose here is based on the multifractal analysis of the signal formed by the succession of bone trabecular thickness and trabecular separation obtained from gray level intensities in the trabecular bone texture to classify the two cases of study.
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https://hal-uphf.archives-ouvertes.fr/hal-03618354
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Submitted on : Thursday, March 24, 2022 - 11:40:57 AM
Last modification on : Friday, August 5, 2022 - 2:54:44 PM

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Mohamed Khider, Boualem Haddad, Abdelmalik Taleb-Ahmed. Multifractal analysis by the large deviation spectrum to detect osteoporosis. 8th International Workshop on Systems, Signal Processing and Their Applications, WoSSPA 2013, May 2013, Algiers, Algeria. ⟨10.1109/WoSSPA.2013.6602346⟩. ⟨hal-03618354⟩

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