1 January 2003 Automatic three-dimensional graph construction of nerve cells from confocal microscopy scans
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J. of Electronic Imaging, 12(1), (2003). doi:10.1117/1.1526102
Abstract
We present a method of automatic graph construction for the description of the geometric structure of nerve cells from 3-D confocal scans. The method consists of tracing the branch center points, in the branch axial direction using as hints the location of difficult regions inside the neuronal branches. The axis were obtained in previous work by computing pairwise vector products of intersecting gradients associated with across-scales validated boundary edge points of the neuronal branches. The axis anchor points are the branch center points, which are estimated as the "center of mass" of all intersecting gradient end points. The difficult regions are the axis anchor points having a high directional variance of vector products contributing to the associated axis. The presented algorithm, which uses all the information obtained from preprocessing, is robust to variable contrast; has little sensitivity to boundary irregularities; is adaptive to variability of branch geometry; and produces a sparse, topology preserving graph of the neuron under investigation. A subsequent surface reconstruction based on this graph (Schmitt et al., 2001) accompanied by the labeling of the graph with geometric measurements would be feasible.
Anca Dima, Michael Scholz, Klaus Obermayer, "Automatic three-dimensional graph construction of nerve cells from confocal microscopy scans," Journal of Electronic Imaging 12(1), (1 January 2003). http://dx.doi.org/10.1117/1.1526102
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KEYWORDS
Neurons

3D image processing

Binary data

Image segmentation

Signal to noise ratio

Confocal microscopy

Volume rendering

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