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M. I. El-Gohary, A. S. A. Mohamed, M. M. Dahab, M. A. Ibrahim, A. A. El-Saied and H. A. Ayoub, “Diagnosis of Epilepsy by Artificial Neural Network,” Journal of Biological Science, Vol. 8, No. 2, 2008, pp. 451-455. doi:10.3923/jbs.2008.451.455

has been cited by the following article:

• TITLE: A Review of Epilepsy Diagnosis Using PET Parameters

  AUTHORS: Yadalam Kiran Kumar, Shashi Bhushan Mehta, Uday Patil

  KEYWORDS: Epilepsy; PET; Asymmetric Index; Standard Uptake Value

  JOURNAL NAME: Journal of Behavioral and Brain Science, Vol.2 No.3, August 31, 2012

  ABSTRACT: Epilepsy is caused by abnormal excessive electric discharges from the neurons in the brain. Epileptic seizures are non- specific responses of the brain to many types of insults. The structural abnormalities causing epilepsy can be identified using various state of art imaging methods. Through a combination of brain activity monitoring, imaging and mapping techniques, physicians can locate the specific area in the brain causing epileptic discharges and identify its location in relation to those areas in the brain controlling vital functions. Positron Emission Tomography (PET) has emerged as a useful tool to identify abnormal metabolic activity of the epileptogenic foci. Parameters like asymmetric index, stan- dard uptake value (SUV) etc obtained by PET are processed and analyzed for identifying the origin of epileptic sei- zures. This paper discuss the techniques used to diagnose in general and to localize the epileptogenic regions using post-processing other features on PET imaging.