A Comparative Study of Brain Connectivity Visualization and Clustering Techniques

Present a novel approach of brain connectivity visualization of white matter pathways and gray matter areas using diffusion tensor imaging and functional magnetic resonance imaging. Clustering is an important tool for creating abstraction and filtration in general and is central representation in particular. While abstraction involves simplification and generalization, filtration here entails clustering. To visualization of brain volumetric using stream tube, stream surface, streamlines or variation of streamlines of nerve bundles of fibers pathways of brain. Different visualization techniques present here that is weighted graph comparison method, three dimensional neural maps represent in web-interface stand-alone approach similar to Google maps that shown with associated names, measurements and link outs of brain neural maps of different regions like corpus callosum, left cingulum and arcuate and a small portion of right arcuate, both cortico-spinal tracts and inferior frontooccipital fasciculi. Different clustering algorithm that is K-means, Spectral Clustering, Normalized Cut Expectation maximization and fuzzy c-means apply on nerve fiber cluster.