Enhanced Regional Clustering Algorithm in Seizure Location Identification

Abstract

Epilepsy is a chronic condition that is characterized by frequent occurrence of seizure. The treatment of epilepsy using anticonvulsants that suppress the rapid neuron spikes in brain is promising; however, a permanent fix is always lacked. The region on brain that is responsible for seizure if identified exactly, the diseased area can be expelled and that could be a permanent fix. Generally, IEEG (Intracranial Electroencephalogram) an invasive procedure is adopted to diagnose the location of seizure, though the results are very reliable and considered as a golden standard, the procedure is a complex and risky one. To overcome these difficulties, fMRI (Functional magnetic resonance imaging) is used to read the internal anatomical and metabolic nature of brain, an algorithm (erKNOTS, enhanced regional K based Numbering Out of Time Slices) that analyse each individual voxel is developed and implemented. The result obtained by the developed algorithm is found to be in agreement with those obtained through IEEG. The findings were further validated with Regional homogeneity and Functional connectivity.