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 specific anatomical
areas. A simple and flexible 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.
%0 Conference Paper
%1 Akers2004
%A Akers, David
%A Sherbondy, Anthony
%A Mackenzie, Rachel
%A Dougherty, Robert
%A Wandell, Brian
%B VIS '04: Proceedings of the conference on Visualization '04
%C Washington, DC, USA
%D 2004
%I IEEE Computer Society
%K Diffusion, Tensor DTI Imaging, Diffusion
%P 377--384
%R http://dx.doi.org/10.1109/VIS.2004.30
%T Exploration of the Brain's White Matter Pathways with Dynamic Queries
%X 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 specific anatomical
areas. A simple and flexible 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.
%@ 0-7803-8788-0
@inproceedings{Akers2004,
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 specific anatomical
areas. A simple and flexible 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.},
added-at = {2007-01-10T11:43:56.000+0100},
address = {Washington, DC, USA},
author = {Akers, David and Sherbondy, Anthony and Mackenzie, Rachel and Dougherty, Robert and Wandell, Brian},
biburl = {https://www.bibsonomy.org/bibtex/2fb13953cf67ddd371c53a59092c9b6f6/bmeyer},
booktitle = {VIS '04: Proceedings of the conference on Visualization '04},
description = {Diffusion Tensor Imaging (DTI)},
doi = {http://dx.doi.org/10.1109/VIS.2004.30},
interhash = {d25b9742e247f850046631d72d938f66},
intrahash = {fb13953cf67ddd371c53a59092c9b6f6},
isbn = {0-7803-8788-0},
keywords = {Diffusion, Tensor DTI Imaging, Diffusion},
pages = {377--384},
publisher = {IEEE Computer Society},
timestamp = {2007-01-10T11:43:56.000+0100},
title = {Exploration of the Brain's White Matter Pathways with Dynamic Queries},
year = 2004
}