Symmetry Based Cluster Approach for Automatic Recognition of the Epileptic Focus in Brain Using PET Scan Image : An Analysis

TL;DR

This paper presents an automated, symmetry-based clustering method for accurately localizing epileptic foci in brain PET images, aiding surgical diagnosis.

Contribution

It introduces a fully automated symmetry-based brain abnormality detection method using PET images, improving localization accuracy for epilepsy diagnosis.

Findings

High accuracy in epileptic focus detection

Automated method reduces manual analysis time

Supports surgical planning with reliable localization

Abstract

Recognition of epileptic focal point is the important diagnosis when screening the epilepsy patients for latent surgical cures. The accurate localization is challenging one because of the low spatial resolution images with more noisy data. Positron Emission Tomography (PET) has now replaced the issues and caring a high resolution. This paper focuses the research of automated localization of epileptic seizures in brain functional images using symmetry based cluster approach. This approach presents a fully automated symmetry based brain abnormality detection method for PET sequences. PET images are spatially normalized to Digital Imaging and Communications in Medicine (DICOM) standard and then it has been trained using symmetry based cluster approach using Medical Image Processing, Analysis & Visualization (MIPAV) tool. The performance evolution is considered by the metric like accuracy of diagnosis. The obtained result is surely assists the surgeon for the automated identification of seizures focus.