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

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).