Neuro-Fuzzy Approach Toward Segmentation of Brain MRI Based on Intensity and Spatial Distribution

Segmentation in image processing finds immense application in various areas. Image processing techniques can be used in medical applications for various diagnoses. In this article, we attempt to apply segmentation techniques to the brain images. Segmentation of brain magnetic resonance images (MRI) can be used to identify various neural disorders. We can segment abnormal tissues from the MRI, which and can be used for early detection of brain tumors. The segmentation, when applied to MRI, helps in extracting the different brain tissues such as white matter, gray matter and cerebrospinal fluid. Segmentation of these tissues helps in determining the volume of these tissues in the three-dimensional brain MRI. The study of volume changes helps in analyzing many neural disorders such as epilepsy and Alzheimer disease. We have proposed a hybrid method combining the classical Fuzzy C Means algorithm with neural network for segmentation.