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Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance

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  • Lahmiri, Salim

Abstract

The main purpose of this work is to explore the usefulness of fractal descriptors estimated in multi-resolution domains to characterize biomedical digital image texture. In this regard, three multi-resolution techniques are considered: the well-known discrete wavelet transform (DWT) and the empirical mode decomposition (EMD), and; the newly introduced; variational mode decomposition mode (VMD). The original image is decomposed by the DWT, EMD, and VMD into different scales. Then, Fourier spectrum based fractal descriptors is estimated at specific scales and directions to characterize the image. The support vector machine (SVM) was used to perform supervised classification. The empirical study was applied to the problem of distinguishing between normal and abnormal brain magnetic resonance images (MRI) affected with Alzheimer disease (AD). Our results demonstrate that fractal descriptors estimated in VMD domain outperform those estimated in DWT and EMD domains; and also those directly estimated from the original image.

Suggested Citation

  • Lahmiri, Salim, 2016. "Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 235-243.
  • Handle: RePEc:eee:phsmap:v:456:y:2016:i:c:p:235-243
    DOI: 10.1016/j.physa.2016.03.046
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    1. Fabbri, Ricardo & Bastos, Ivan N. & Neto, Francisco D. Moura & Lopes, Francisco J.P. & Gonçalves, Wesley N. & Bruno, Odemir M., 2014. "Multi-q pattern classification of polarization curves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 332-339.
    2. Fabbri, Ricardo & Gonçalves, Wesley N. & Lopes, Francisco J.P. & Bruno, Odemir M., 2012. "Multi-q pattern analysis: A case study in image classification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(19), pages 4487-4496.
    3. Ruiz Vargas, E. & Mitchell, D.G.V. & Greening, S.G. & Wahl, L.M., 2014. "Topology of whole-brain functional MRI networks: Improving the truncated scale-free model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 151-158.
    4. Kilic, Ilker & Kayacan, Ozhan, 2012. "Generalized ICM for image segmentation based on Tsallis statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4899-4908.
    5. Lahmiri, Salim, 2015. "Long memory in international financial markets trends and short movements during 2008 financial crisis based on variational mode decomposition and detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 130-138.
    6. Florindo, João B. & Sikora, Mariana S. & Pereira, Ernesto C. & Bruno, Odemir M., 2013. "Characterization of nanostructured material images using fractal descriptors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1694-1701.
    7. Gonçalves, Wesley Nunes & Machado, Bruno Brandoli & Bruno, Odemir Martinez, 2014. "Texture descriptor combining fractal dimension and artificial crawlers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 358-370.
    8. Barbieri, Andre L. & de Arruda, G.F. & Rodrigues, Francisco A. & Bruno, Odemir M. & Costa, Luciano da Fontoura, 2011. "An entropy-based approach to automatic image segmentation of satellite images," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(3), pages 512-518.
    9. Ahammer, H. & Kroepfl, J.M. & Hackl, Ch. & Sedivy, R., 2011. "Fractal dimension and image statistics of anal intraepithelial neoplasia," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 86-92.
    10. Oliveira, Marcos William da S. & Casanova, Dalcimar & Florindo, João B. & Bruno, Odemir M., 2014. "Enhancing fractal descriptors on images by combining boundary and interior of Minkowski dilation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 41-48.
    11. Provata, A. & Katsaloulis, P. & Verganelakis, D.A., 2012. "Dynamics of chaotic maps for modelling the multifractal spectrum of human brain Diffusion Tensor Images," Chaos, Solitons & Fractals, Elsevier, vol. 45(2), pages 174-180.
    12. Spodarev, Evgeny & Straka, Peter & Winter, Steffen, 2015. "Estimation of fractal dimension and fractal curvatures from digital images," Chaos, Solitons & Fractals, Elsevier, vol. 75(C), pages 134-152.
    13. De Vico Fallani, Fabrizio & Chessa, Alessandro & Valencia, Miguel & Chavez, Mario & Astolfi, Laura & Cincotti, Febo & Mattia, Donatella & Babiloni, Fabio, 2012. "Community structure in large-scale cortical networks during motor acts," Chaos, Solitons & Fractals, Elsevier, vol. 45(5), pages 603-610.
    14. Klonowski, W. & Pierzchalski, M. & Stepien, P. & Stepien, R. & Sedivy, R. & Ahammer, H., 2013. "Application of Higuchi’s fractal dimension in analysis of images of Anal Intraepithelial Neoplasia," Chaos, Solitons & Fractals, Elsevier, vol. 48(C), pages 54-60.
    15. Vieira, Vilson & Fabbri, Renato & Sbrissa, David & da Fontoura Costa, Luciano & Travieso, Gonzalo, 2015. "A quantitative approach to painting styles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 110-129.
    16. Chauveau, Julien & Rousseau, David & Richard, Paul & Chapeau-Blondeau, François, 2010. "Multifractal analysis of three-dimensional histogram from color images," Chaos, Solitons & Fractals, Elsevier, vol. 43(1), pages 57-67.
    17. Florindo, João Batista & Bruno, Odemir Martinez, 2012. "Fractal descriptors based on Fourier spectrum applied to texture analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4909-4922.
    18. Torres Hoyos, F. & Martín-Landrove, M., 2012. "3-D in vivo brain tumor geometry study by scaling analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1195-1206.
    19. Colangeli, Matteo & Rugiano, Francesco & Pasero, Eros, 2014. "Pattern recognition at different scales: A statistical perspective," Chaos, Solitons & Fractals, Elsevier, vol. 64(C), pages 48-66.
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    Cited by:

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    3. Du, Pei & Wang, Jianzhou & Yang, Wendong & Niu, Tong, 2020. "Point and interval forecasting for metal prices based on variational mode decomposition and an optimized outlier-robust extreme learning machine," Resources Policy, Elsevier, vol. 69(C).
    4. Lahmiri, Salim, 2017. "Parkinson’s disease detection based on dysphonia measurements," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 98-105.
    5. Zhang, Hong-Yan & Kang, Ming-Cui & Li, Jing-Qiang & Liu, Hai-Tao, 2017. "R/S analysis of reaction time in Neuron Type Test for human activity in civil aviation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 859-870.
    6. Salim Lahmiri, 2016. "Features selection, data mining and finacial risk classification: a comparative study," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(4), pages 265-275, October.

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