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A method for the automatic segmentation of autoradiographic image stacks and spatial normalization of functional cortical activity patterns.

Johannes Mohr·Andreas Hess·Michael Scholz·Klaus Obermayer
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Abstract

This paper introduces two new methods for the automatic anatomical and functional analysis of neurobiological autoradiographic image stacks, such as 2-fluoro-deoxyglucose (2FDG) images. The difficulty in the evaluation of these "2(1/2)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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AnimalsAutoradiographyCerebral CortexFluorodeoxyglucose F18Imaging, Three-DimensionalRatsJournal ArticleResearch Support, Non-U.S. Gov't

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Johannes Mohr, Andreas Hess, Michael Scholz, Klaus Obermayer. 2004-03-15. A method for the automatic segmentation of autoradiographic image stacks and spatial normalization of functional cortical activity patterns.. https://doi.org/10.1016/j.jneumeth.2003.10.015

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