Exploration of the Brain's White Matter Pathwayswith Dynamic Queries
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David Akers
Stanford University |
Anthony Sherbondy
Stanford University |
Rachel Mackenzie
Stanford University |
Robert Dougherty
Stanford University |
Brian Wandell
Stanford University |
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IEEE Visualization 2004 (This paper has been extended in our IEEE TVCG 2005 article.) |
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Video (interface demonstration) |
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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-shaped regions (or volumes
of interest) to selectively display pathways that pass through
specc anatomical areas. A simple and exible query language
allows for arbitrary combinations of these queries using Boolean
logic operators. Queries can be further restricted by numerical path
properties such as length, mean fractional anisotropy, and mean
curvature.
By precomputing the pathways and their statistical properties,
we obtain the speed necessary for interactive question-andanswer
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.
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Figure 1: The
corona radiata. Our system uses dynamic queries to find
structure in neural pathways suggested by MR tractography.
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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. | |||||
David Akers | Last updated 17 Oct 2004 |