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Neuroanatomical Atlases in MIPAV
| Overview |
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We describe
the Talairach atlas-based software tool and atlas data released
in the download
section. The tool is a plug-in for the MIPAV
software package that provides atlas-based labeling in the Talaraich
coordinate space. It allows to easily identify subregions of the
brain and measure their volume (see the quick tutorial).
It includes labels for
148 different substructures of the brain at various scales, obtained
from
the Talairach
Daemon database, along with a set of volumetric images of the
labels.
Work is under way to
integrate the ICBM
template labels, and to provide additional tools for creating
and editing atlas data in MIPAV.
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| Acknowledgments |
The atlases have been created
from data previously released by J.L. Lancaster et al. (for the Talairach
Daemon) and the Montreal Neurological
Institute (for the ICBM
template).
The plug-in for Mipav has
been developped in collaboration with Matthew McAuliffe and the
MIPAV development team at NIH.
This data has been further
processed and tested for the integration into Mipav, to correct some small
artefacts or labelling mistakes. However, as all labels have not been
studied in detail, we recommend users to check the correctness of the
labels before use. |
| Documentation |
| The MIPAV team has created a detailed
and comprehensive technical
guide for the Talairach transformation tools and the standard procedure
for volumetric measurements. |
| Tutorial:
measuring the volume of substructures |
| Step
1: After
installing the plug-in in MIPAV, open the image to study and launch
the Talairach Transform plug-in.
(PlugIns -
File > Install Plugin; File > Open new image; PlugIns >
Algorithms > TalairachTransform) |
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| Step
2: Perform
the ACPC alignment, followed by the Talairach alignment: locate
the Anterior and Posterior Commissures and other important points,
and let the algorithm transform the image into Talairach space.
(in the Talairach
Transform window: press ACPC and follow the instructions, then
press Talairach and follow the instructions) |
 
From original to Talairach space
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| Step
3: Load
the labels for the regions of interest on the Talairach image.
(VOI > Open
VOI) |
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| Step
4: Segment
White Matter, Gray Matter and CSF on the original image.
(Algorithm
> Fuzzy C-means > Single channel) |
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| Step
5: Transform
the labels from Talairach to original space.
(in the Talairach
Transform window: select Talairach image; Tlrc to orig; press
compute) |
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| Step
6: Copy
the transformed labels to the segmented image.
(Edit >
Copy VOI; Edit > Paste VOI) |
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| Step
7: Compute
the volume of Gray Matter inside the labels of interest.
(VOI > Statistics
Generator; select the VOIs to process int the VOI Selection tab;
select Volume or # of Voxels in the Statistics option tab, and
check Pixel Exclusion to exclude pixels outside the gray matter
intensity in the segmented image) |
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More
possibilities |
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The VOIs in Mipav can be manipulated, customized and
altered in a variety of ways. Special labels can easily be created,
edited and saved for the purpose of a particular study.
We wish to provide more detailled and abundant labeling
information, so please contact us if you want to had your own labels
and atlases to those we already created.
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| References |
- J. Talairach and P. Tournoux. Co-Planar Stereotaxic Atlas of the
Human Brain. Thieme, 1988.
- J.L. Lancaster, J.L. Summerlin, L. Rainey, C.S. Freitas and P.T. Fox.
The Talairach Daemon, a database server for talairach atlas labels.
Neuroimage, 5(4), 1997.
- P.L. Bazin, W. Gandler, M. McAuliffe and D. Pham, Free Software
Tools for Atlas-based Volumetric Neuroimage Analysis, Proceedings
of SPIE Medical Imaging conference, 2005.
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© Copyright 2005-2008 | All Rights Reserved | Johns Hopkins
University & Laboratory of Medical Image Computing
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