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Classification of brain SPECT imaging using 3D local multifractal spectrum for epilepsy detection

  • Review Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Multifractal spectrum analysis is a discriminating tool that may distinguish volunteers and epileptic patients. In this study, our aim was to detect epileptogenic sources by computing the singularity spectrum.

Materials and methods

Multifractal analysis based on generalized concepts of fractals has been applied to evaluate biological tissues composed of complex structures. This analysis can provide a precise quantitative description for a broad range of heterogeneous phenomena. This study investigates the possibility of using a mathematical model (multifractal analysis) for image texture to detect the underlying source changes on SPECT images. Previously, reported on application of 3D multifractal analysis to describe the multifractal character of brain SPECT (Single-Photon Emission Computed Tomography) images and we showed that the multifractal spectrum is a discriminating tool to distinguish volunteers and epileptic patients. The experiment is divided into two phases. First, we developed a 3D method for the singularity spectrum compute. In the test phase, we applied this multifractal spectrum to the detection of epileptogenic sources in SPECT images.

Results

The results obtained on a group of seven patients show that the proposed method is feasible and the results are encouraging. The epileptic fit sources obtained using the system were in agreement with the opinion of expert diagnosticians.

Conclusion

Multifractal spectrum analysis provides a means of detecting and localizing epileptogenic foci in brain SPECT scans.

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Authors and Affiliations

  1. INSERM, U703, ITM, Pavillon Vancostenobel, CHRU Lille, 59037, Lille, France

    R. Lopes, P. Dubois, N. Makni & N. Betrouni

  2. LAGIS, UMR CNRS 8146, USTL, Villeneuve d’Ascq, France

    R. Lopes, N. Makni & S. Maouche

  3. Neurophysiology Department, Univeristy Hospital, CHRU Lille, Lille, France

    W. Szurhaj

Authors
  1. R. Lopes
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  2. P. Dubois
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  3. N. Makni
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  4. W. Szurhaj
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  5. S. Maouche
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  6. N. Betrouni
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Corresponding author

Correspondence to R. Lopes.

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Lopes, R., Dubois, P., Makni, N. et al. Classification of brain SPECT imaging using 3D local multifractal spectrum for epilepsy detection. Int J CARS 3, 341–346 (2008). https://doi.org/10.1007/s11548-008-0227-4

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  • DOI: https://doi.org/10.1007/s11548-008-0227-4

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