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A Method for the Automatic Segmentation Autoradiographic Image Stacks and Spatial Normalization of Functional Cortical Activity Data
Citation key Mohr2004
Author Mohr, J. and Hess, A. and Scholz, M. and Obermayer, K.
Pages 45 – 58
Year 2004
DOI 10.1016/j.jneumeth.2003.10.015
Journal J. Neurosci. Methods
Volume 134
Number 1
Publisher Elsevier
Abstract 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.
Bibtex Type of Publication Selected:multimodal
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