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- J. Mohr, A. Hess, M. Scholz,
and K. Obermayer. A Method for the Automatic Segmentation Autoradiographic
Image Stacks and Spatial Normalization of Functional Cortical Activity Data.
.
J. Neurosci. Methods, 134:45-58, 2004.
(FTP Gzipped PDF, 2164 kb)
This paper introduces two new methods for the automatic anatomical
and funct ional analysis of neurobiological autoradiographic image stacks,
such as 2-fluoro-deoxyglucose (2FDG) images. The difficulty in the evaluation
of these 2 ? D datasets is that they do not inherently represent a continuous
3D data volume (as generated by MRI or CT), but consist of a stack of images
from single tissue slices, suffering from unavoidable preparation artifacts.
In the first part of the paper, a semi-automatic segmentation method is
presented which generates a 3D surface model of certain brain structures and
which is robust against different cutting directions with respect to the
brain coordinate system. The method saves man-hours compared to manual
segmentation and the results are highly reproducible. In the second part, a
fully automatic method for the extraction, analysis and 3D visualization of
functional information is described, which allows not only a more accurate
localization of activation sites, but also greatly enhances the comparability
of different individuals. Results are shown for 2FDG autoradiographs from rat
brains under acoustical stimulation.
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