Reconstruction of a neuron from SBFSEM: Tools, Reliability, Accuracy and Efficiency
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1
Max Planck Institute for Neurobiology, Cortical Column in Silico Research Group, Germany
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2
University of Heidelberg, Interdisciplinary Center for Scientific Computing, Germany
In this presentation we demonstrate a new software package named NEUROSTRUCT custom designed for large-scale image datasets obtained bySerial Block-Face Scanning Electron Microscopy (SBFSEM)[1]. The computational model is processing data in voxel pipelines and is based on GPU computing [2]. We will show in detail the working pipeline for obtaining a final 3D reconstruction result from SBFSEM data, fully independent of initial data size, in an efficient manner. The software is designed to focus on the recognition of dendrites and spine morphologies at finest detail. In this respect SBFSEM datasets sizing many hundred GBs can be readily reconstructed. We will also present a study of reliability and accuracy of the computational results by comparing them with a reference dataset generated by manual segmentations. Performance tests on large scale datasets to demonstrate the efficiency of our pipeline will also be discussed. Finally, we will show a few preliminary results of a L5B cortical neuron reconstruction being imaged by SBFSEM (cell size ~100 x 120 x 500 μm3; microscope’s voxel resolution 25x25x30 nm3). All significant morphological details of the neuron and its dendritic spines are revealed at finest detail (see Fig. 1), thereby making the evaluation of spines at large scale feasible.
Fig. 1: Computational 3D Reconstruction of a L5B neuron from SBFSEM Microscopy overlaying a light microscopy projection of the corresponding mouse cell. (Close-up) Zoom on three distinct spines connected toa dendritic branch.
References
[1] Winfried Denk and Heinz Horstmann,“Serial Block-Face Scanning Electron Microscopy to Reconstruct Three-Dimensional Tissue Nanostructure”, PLoS Biology, Volume 2, Issue 11 pp. 1900-1908, November 2004.
[2] S. Lang, P. Drouvelis, E. Tafaj, P. Bastian and B. Sakmann,“Fast extraction of neuron morphologies from large-scale electron microscopic image stacks”, submitted for publication to Journal of Computational Neuroscience.
Keywords:
computational neuroscience
Conference:
Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010.
Presentation Type:
Presentation
Topic:
Bernstein Conference on Computational Neuroscience
Citation:
Drouvelis
P,
Kurz
T,
Bastian
P,
Sakmann
B and
Lang
S
(2010). Reconstruction of a neuron from SBFSEM: Tools, Reliability, Accuracy and Efficiency.
Front. Comput. Neurosci.
Conference Abstract:
Bernstein Conference on Computational Neuroscience.
doi: 10.3389/conf.fncom.2010.51.00055
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Received:
16 Sep 2010;
Published Online:
23 Sep 2010.
*
Correspondence:
Dr. Panos Drouvelis, Max Planck Institute for Neurobiology, Cortical Column in Silico Research Group, Munich, Germany, Panagiotis.Drouvelis@iwr.uni-heidelberg.de