An optimized set of 3D fractal and multifractal features for the epileptogenic focus characterization in SPECT imaging

Author

Lopes, R. ; Vermandel, M. ; Dewalle-Vignion, A.S. ; Maouche, S. ; Betrouni, N.

Author_Institution

Inserm, CHRU Lille, Lille, France

fYear

2009

fDate

June 28 2009-July 1 2009

Firstpage

550

Lastpage

553

Abstract

Fractal geometry may be an efficient tool for texture analysis in medical imaging. However its application is primarily restricted to 2D cases and at the only use of an approximation method of the fractal dimension (FD). Recently, multifractal analysis has showed interesting results in this field. This study focuses on the use of an optimized set of 3D fractal and multifractal features for the epileptogenic focus characterization in SPECT imaging. Our results showed that this optimized set, compared to various texture features, improved the classification rate by Support Vector Machines (SVM). Moreover, results were significantly better than the clinical method: SISCOM (Substraction Ictal SPECT Co-registred to MRI).

Keywords

fractals; image classification; image texture; medical image processing; single photon emission computed tomography; support vector machines; 3D fractal features; SPECT imaging; classification; epileptogenic focus characterization; fractal dimension; multifractal features; support vector machines; texture analysis; Approximation methods; Biomedical imaging; Epilepsy; Focusing; Fractals; Geometry; Image analysis; Image texture analysis; Support vector machine classification; Support vector machines; 3D fractal and mutlifractal analysis; SPECT imaging; classification; epilepsy;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on

Conference_Location

Boston, MA

ISSN

1945-7928

Print_ISBN

978-1-4244-3931-7

Electronic_ISBN

1945-7928

Type

conf

DOI

10.1109/ISBI.2009.5193106

Filename

5193106