Electron Microscopy Visualisation

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Volume visualization in serial electron microscopy using local variance

Serial electron microscopy (EM) has the ability to improve three-dimensional imaging dramatically by providing nanometer-scale resolution. Serial EM data sets of brain tissue can potentially be used to reconstruct the complex structure of biological neural networks. These data sets consist of gigabytes of volumetric data densely packed with anatomical information. This makes three-dimensional EM data sets difficult to visualize.These are new methods for visualizing EM data sets using a novel transfer function based on the local variance of volumetric features.

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Java, JOGL, enRoute

Project development

Institution: Beckman Institute for Advanced Science and Technology, Department of Computer Science, University of Illinois at Urbana-Champaign

We would like to thank Hans-Jörg Schulz for his input. This work is supported by the following grants: Caleydoplex (P22902, FWF), Tumorheterogeneity (GZ:A3–22.M-5/2012–21, state of Styria), IMGuS (Austria Wirtschaftsservice), and inGeneious (385567, FFG).