Ieee Transactions on Visualization and Computer Graphics 1 Exploring Connectivity of the Brain's White Matter with Dynamic Queries
Ieee Transactions on Visualization and Computer Graphics 1 Exploring Connectivity of the Brain's White Matter with Dynamic Queries
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通讯作者:
Anthony J. Sherbondy;David Akers;Rachel Mackenzie;R. Dougherty;B. Wandell
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作者:
Anthony J. Sherbondy;David Akers;Rachel Mackenzie;R. Dougherty;B. Wandell
Fig. 1. The corona radiata. Our system uses dynamic queries to find structure in neural pathways suggested by MR tractography. 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.