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




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 10-20nm in the x and y- and 30nm in z-direction. Consequently, a tissue block of 1mm3 (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 semiautomated 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.

Author(s): Macke, JH. and Maack, N. and Gupta, R. and Denk, W. and Schölkopf, B. and Borst, A.
Journal: Journal of Neuroscience Methods
Volume: 167
Number (issue): 2
Pages: 349-357
Year: 2008
Month: January
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
DOI: 10.1016/j.jneumeth.2007.07.021
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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  title = {Contour-propagation Algorithms for Semi-automated Reconstruction of Neural Processes},
  author = {Macke, JH. and Maack, N. and Gupta, R. and Denk, W. and Sch{\"o}lkopf, B. and Borst, A.},
  journal = {Journal of Neuroscience Methods},
  volume = {167},
  number = {2},
  pages = {349-357},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = jan,
  year = {2008},
  month_numeric = {1}