Abstract. Visualizing the human brain using diffusion tensor magnetic resonance imaging (DT-MRI) data has been a key technique to study the structure of the human brain and its connectivity. The challenge is to find a method that best exploits the data and serves as a model for visualization and connectivity analysis. This paper presents a novel method of visualizing the human brain structure with a minimum spanning tree using DT-MRI data. The human brain is modeled as a graph in which each vertex represents a brain voxel and each edge represents connectivity between a pair of neighboring brain voxels, resulting in each vertex having 26 weighted connections with adjacent voxels. The weight of an edge is calculated from the DT-MRI data with a higher weight assigned to an edge that are more likely aligned with nerve fiber trajectories. The method then grows a minimum spanning tree representing paths of the nerve fiber bundles. The resultant minimum spanning tree is consistent with the...