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  Contour-propagation Algorithms for Semi-automated Reconstruction of Neural Processes

Macke, J., Maack, N., Gupta, R., Denk, W., Schölkopf, B., & Borst, A. (2008). Contour-propagation Algorithms for Semi-automated Reconstruction of Neural Processes. Journal of Neuroscience Methods, 167(2), 349-357. doi:10.1016/j.jneumeth.2007.07.021.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CA9D-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-96FC-5
Genre: Journal Article

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 Creators:
Macke, JH1, 2, 3, Author              
Maack, N, Author
Gupta, R, Author
Denk, W, Author
Schölkopf, B2, 3, Author              
Borst, A, Author              
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: A new technique, “serial block face scanning electron microscopy” (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10–20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm3(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated.

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 Dates: 2008-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.jneumeth.2007.07.021
BibTex Citekey: 4667
 Degree: -

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Title: Journal of Neuroscience Methods
  Other : J. Neurosci. Meth.
Source Genre: Journal
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Publ. Info: Amsterdam : Elsevier
Pages: - Volume / Issue: 167 (2) Sequence Number: - Start / End Page: 349 - 357 Identifier: ISSN: 0165-0270
CoNE: https://pure.mpg.de/cone/journals/resource/954925480594