Empirical Inference Article 2008

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
Bibtex Type: Article (article)
DOI: 10.1016/j.jneumeth.2007.07.021
Digital: 0
Electronic Archiving: grant_archive
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex

@article{4667,
  title = {Contour-propagation Algorithms for Semi-automated Reconstruction of Neural Processes},
  journal = {Journal of Neuroscience Methods},
  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 10-20nm 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.},
  volume = {167},
  number = {2},
  pages = {349-357},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = jan,
  year = {2008},
  slug = {4667},
  author = {Macke, JH. and Maack, N. and Gupta, R. and Denk, W. and Sch{\"o}lkopf, B. and Borst, A.},
  month_numeric = {1}
}