Fractal features for localization of temporal lobe epileptic foci using SPECT imaging

Single photon emission computed tomography (SPECT) is an accurate imaging method for the diagnosis of refractory partial epilepsy. Two scans are carried out: interictal and ictal. The interest of this method is to provide an image in the ictal period, which allows hyperperfused areas linked to the seizure to be localized. The epileptic foci localization is improved by subtracting the two acquisitions (subtracted ictal SPECT: SIS). In some cases, the SIS method is not effective and does not isolate the seizure foci. In this article, we investigate a new method based on texture analysis using fractal geometry features. Fractal geometry features were extracted from each scan in order to quantify the heterogeneity change resulting from the hyperperfusion. A support vector machine (SVM) classification algorithm was used to classify the voxels into two classes: focal and healthy. Quantitative evaluation was performed on simulated images and clinical images from 22 patients with temporal lobe epilepsy. Results on both experiments showed that the proposed method is more specific and more sensitive than the SIS method.