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  Contour-propagation algorithms for semi-automated reconstruction of neural processes

Macke, J. H., 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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Macke, Jakob H., Author
Maack, Nina, Author
Gupta, Rocky, Author
Denk, Winfried1, Author           
Schölkopf, Bernhard, Author
Borst, Alexander, Author
Affiliations:
1Department of Biomedical Optics, Max Planck Institute for Medical Research, Max Planck Society, ou_1497699              

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Free keywords: Circuit reconstruction software; Contour detection; Algorithm; Image segmentation; Serial block−face scanning electron microscopy; Neural circuits; Fly visual system
 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 mm(3)(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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Language(s): eng - English
 Dates: 2007-03-062007-07-262007-08-102008-01-30
 Publication Status: Issued
 Pages: 9
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 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