The soft computing techniques solve the major localization problems in optimization of biomedical images. We have developed an automatic method aimed first at segmentation of MRI brain images by denoising with Discrete Curvelet Transform. Then clustering of denoised images using Fuzzy C-means clustering localized the abnormality by simulating the anatomical structure. The statistical analysis confirmed the validity of the algorithm. The abnormality in localization compared with microarray gene expression evaluation also showed variations which will be helpful for the development of gene module based neuroimaging advancements.