Exploring Connectivity of the Brain's White Matter with Dynamic Queries

Exploring Connectivity of the Brain's White Matter with Dynamic Queries
Anthony Sherbondy Stanford University	David Akers Stanford University	Rachel Mackenzie Stanford University	Robert Dougherty Stanford University	Brian Wandell Stanford University
To appear in Transactions on Visualization and Computer Graphics in 2005 (This is an extended version of our IEEE Visualization 2004 paper.)
Paper Draft PDF (7.5 MB)
Video (interface demonstration) Quicktime MOV (232 MB)
Software Web site
Abstract Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging method that can be used to measure local information about the structure of white matter within the human brain. Combining DTI data with the computational methods of MR tractography, neuroscientists can estimate the locations and sizes of nerve bundles (white matter pathways) that course through the human brain. Neuroscientists have used visualization techniques to better understand tractography data, but they often struggle with the abundance and complexity of the pathways. In this paper, we describe a novel set of interaction techniques that make it easier to explore and interpret such pathways. Specifically, our application allows neuroscientists to place and interactively manipulate box- or ellipsoid-shaped regions to selectively display pathways that pass through specific anatomical areas. These regions can be used in coordination with a simple and flexible query language which allows for arbitrary combinations of these queries using Boolean logic operators. A representation of the cortical surface is provided for specifying queries of pathways that may be relevant to gray matter structures, and for displaying activation information obtained from functional magnetic resonance imaging. By precomputing the pathways and their statistical properties, we obtain the speed necessary for interactive question-and-answer sessions with brain researchers. We survey some questions that researchers have been asking about tractography data and show how our system can be used to answer these questions efficiently.

Figure 1: The corona radiata. Our system uses dynamic queries to find structure in neural pathways suggested by MR tractography.

Figure 3: Sequence of dynamic queries identifying the spatial organization of fiber pathways. a) All 13,000 pathways computed using the STT algorithm. Patterns are difficult to discern because of all the visual clutter. b) Using a length filter, we show only the pathways that are greater than 40mm in length (30 percent of the total number of pathways). c) By placing VOI 1 in the scene, we show only the pathways that pass through the internal capsule (bottom). d) By placing VOIs 2 and 3, we obtain a picture showing connections between 1 and either 2 or 3.

Figure 4: Constraining VOI motion to the cortical surface. a) The cortical surface with an ellipsoid-shaped VOI placed on a section of the back of the brain. b) A smoothed representation of the cortical surface with a projection of the same VOI. Both surfaces present a higher intensity gray level for gyri and a lower intensity gray for the sulci. The smoothed surface allows the neuroscientist to manipulate a VOI on the cortical surface without the bumps and folds of the original surface obscuring the view to the VOI.
David Akers \| Last updated 14 Jan 2005