Browsing by Author "Jennane, Rachid"

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    Fractal analysis of bone radiographs correlated with histomorphometry
    (2011) Harrar, Khaled; Hamami, Latifa; Jennane, Rachid
    The bone fragility in osteoporosis is multifactorial and complex. At present, fracture risk prediction in the individual patient relies chiefly on bone mineral density (BMD) measurements. However, many lines of evidence indicate that the decreased bone strength…
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    Oriented fractal analysis for improved bone microarchitecture characterization
    (Elsevier, 2017) Harrar, Khaled; Jennane, Rachid; Zaouchi, Karima; Janvier, Thomas; Toumi, Hechmi; Lespessailles, Eric
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    Piecewise whittle estimator for trabecular bone radiograph characterization
    (Elsevier, 2013) Harrar, Khaled; Hamami, Latifa; Lespessailles, Eric; Jennane, Rachid
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    Quantification of Trabecular Bone Porosity on X-Ray Images
    (2015) Harrar, Khaled; Jennane, Rachid
    Osteoporosis is a disease characterized by low bone mass and deterioration of the micro-architecture of the bone tissue, which lead to increased bone fragility and therefore, an increased risk of fracture. The purpose of this work is to quantify the porosity of radiographic bone images in order to characterize osteoporosis. Two methods are used to characterize radiographic bone images, lacunarity and star volume distribution. The first method is based on fractal analysis and the second on the evaluation of the bone medullar space. 2D bone radiographic images from two populations composed of 80 control subjects and 80 patients with osteoporotic fractures are analyzed. The results show a good discrimination between the two groups
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    ROI impact on the characterization of knee osteoarthritis using fractal analysis
    (2015) Janvier, Thomas; Toumi, Hechmi; Harrar, Khaled; Lespessailles, Eric; Jennane, Rachid
    This paper presents a preliminary study of the influence of the positioning of Regions Of Interest (ROI) for the characterization of bone texture on radiographs for the diagnosis of knee OsteoArthritis (OA) progression. Characterization of the bone texture is of great interest to doctors because it would improve the prognostic in the clinical routine. In general, studies mainly focus on the descriptors while neglecting the choice of ROI positioning. Using fractal descriptors, the objective of this work is to highlight the impact of the ROI for the diagnosis of knee OA by considering the couple (descriptor, ROI). This study was performed over 1054 knees from 616 subjects composed of stable and progressor patients. Achieved statistical tests demonstrated the importance of the choice of the ROI to improve the clinical diagnosis
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    Texture Analysis: A comparison between Multifractal Spectrum with Legendre Transform and the Box-Counting Method
    (2013) Khider, Mohamed; Harrar, Khaled; Jennane, Rachid; Haddad, Boualem
    Several studies have shown the possibilities offered by multifractal analysis in image processing, particularly for classification of heterogeneous texture with a great complexity in the structure. Indeed, in most cases, the mode of multifractal spectrum is used for classification; in this work we propose two different methods to estimate this spectrum. This paper focuses on the classification of Brodatz textures using multifractal analysis. Two methods are considered. The first method is based on the multifractal formalism of Frish and Parisi through the Legendre transform, the second one is a direct method based on the box-counting algorithm. For both approaches, we used the multiresolution coefficients of the wavelet transform, with the Gaussian first order derivative to find singularity exponents in the direct method, and the leaders coefficients in the case of the multifractal formalism. The Legendre transform was used to estimate the multifractal spectrum, while the box-counting method was used to compute the Hausdorff dimension of sets of the same degree of singularity. Results demonstrate that it is more interesting in some cases to use the box-counting method than the Legendre transform to obtain a more accurate spectrum, as in the case of bimodal spectrum
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    Trabecular Texture Analysis Using Fractal Metrics for Bone Fragility Assessment
    (World Academy of Science, Engineering and Technology, 2015) Harrar, Khaled; Jennane, Rachid
    The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an age-matched 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