Detection of WML in MRI Brain Images using Neuro-Fuzzy Inference System?

White Matter Lesions (WMLs) are small areas of dead cells found in the parts of the brain. In general, it is difficult for medical experts to accurately quantify the WMLs due to decreased contrast between White Matter (WM) and Grey Matter (GM) in MRI brain images. The main aim is to detect the White Matter Lesions present in MRI brain images which may result in memory loss or even death. WML detection process includes the following stages: 1. Image preprocessing, 2. Clustering (Fuzzy c-means clustering (FCM), Geostatistical Possibilistic clustering (GPC), Geostatistical Fuzzy clustering (GFCM) and Neuro-Fuzzy Inference system (NFIS)).Geostatistical Fuzzy C-means Clustering(GFCM) algorithm which is 91.17% accurate and less sensitive to noise o v e r FCM a nd GPC but there will be slight noise present at output and it detects false lesions also. To o v e r c ome this and to make detection more accurate Neuro- Fuzzy inference system is proposed which is found to be 94.12% accurate over GFCM.