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MRI Texture-Based Classification of Dystrophic Muscles. A Search for the Most Discriminative Tissue Descriptors

  • Dorota DudaEmail author
  • Marek Kretowski
  • Noura Azzabou
  • Jacques D. de Certaines
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9842)

Abstract

The study assesses the usefulness of various texture-based tissue descriptors in the classification of canine hindlimb muscles. Experiments are performed on T2-weighted Magnetic Resonance Images (MRI) acquired from healthy and Golden Retriever Muscular Dystrophy (GRMD) dogs over a period of 14 months. Three phases of canine growth and/or dystrophy progression are considered. In total, 39 features provided by 8 texture analysis methods are tested. Features are ranked according to their frequency of selection in a modified Monte Carlo procedure. The top-ranked features are used in differentiation (i) between GRMD and healthy dogs at each phase of canine growth, and (ii) between three phases of dystrophy progression in GRMD dogs. Three classifiers are applied: Adaptive Boosting, Neural Networks, and Support Vector Machines. Small sets of selected features (up to 10) are found to ensure highly satisfactory classification accuracies.

Keywords

Golden Retriever Muscular Dystrophy (GRMD) Duchenne Muscular Dystrophy (DMD) Texture analysis Feature selection Classification MRI T2 

Notes

Acknowledgments

This work was performed under the auspices of the European COST Action BM1304, MYO-MRI. It was also performed in the framework of the grant S/WI/2/2013 (Bialystok University of Technology), founded by the Polish Ministry of Science and Higher Education.

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© IFIP International Federation for Information Processing 2016

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Authors and Affiliations

  • Dorota Duda
    • 1
    Email author
  • Marek Kretowski
    • 1
  • Noura Azzabou
    • 2
    • 3
  • Jacques D. de Certaines
    • 2
    • 3
  1. 1.Faculty of Computer ScienceBialystok University of TechnologyBialystokPoland
  2. 2.Institute of Myology, Nuclear Magnetic Resonance LaboratoryParisFrance
  3. 3.CEA, I2BM, MIRCen, NMR LaboratoryParisFrance

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