Integrated Visualization of Human Brain Connectome Data

Visualization plays a vital role in the analysis of multi-modal neuroimaging data. A major challenge in neuroimaging visualization is how to integrate structural, functional and connectivity data to form a comprehensive visual context for data exploration, quality control, and hypothesis discovery. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomic structure. New surface texture techniques are developed to map non-spatial attributes onto the brain surfaces from MRI scans. Two types of non-spatial information are represented: (1) time-series data from resting-state functional MRI measuring brain activation; (2) network properties derived from structural connectivity data for different groups of subjects, which may help guide the detection of differentiation features. Through visual exploration, this integrated solution can help identify brain regions with highly correlated functional activations as well as their activation patterns. Visual detection of differentiation features can also potentially discover image based phenotypic biomarkers for brain diseases

Visualizing white matter fiber tracts with optimally fitted curved dissection surfaces

White matter fiber tractography from diffusion tensor imaging (DTI) is, in general, visualized as 3D lines or tubes together with 2D anatomical MR slices or surfaces. However, determining the exact location of the fiber tracts in their surrounding anatomy is still unsolved. Rendering the embedding anatomy of fiber tracts provides new insight into the exact spatial arrangement of fiber bundles, their spatial relation, and tissue properties surrounding the tracts [SSA*08]. We propose a virtual Klingler dissection method of brain white matter creating curved dissection surfaces locally parallel to user specified fiber bundles. To achieve this effect in computer visualization, we create free-form clipping surfaces that align with the fiber structure of the brain and texture these according to structures they intersect or align with. An optimal view on the naturally embedding curved anatomical structure of the surrounding tissue enables the study of location and course of fiber bundles and the specific relation between different fiber systems in the brain. Indication of the local fiber orientation on the dissected brain surface leads to a representation of both, structural and directional information. The system is demonstrated on a human DTI dataset illustrating the dissection of the sub-insular white matter