Lucian Carata, Dan Shao, Markus Hadwiger, Eduard GröllerORCID iD
Improving the Visualization of Electron-Microscopy Data Through Optical Flow Interpolation
In Proceedings of the 27th Spring Conference on Computer Graphics, pages 1-8. April 2011.
[Paper]

Information

  • Publication Type: Conference Paper
  • Workgroup(s)/Project(s):
  • Date: April 2011
  • Organization: Spring Conference on Computer Graphics
  • Location: Viničné, Slovak Republic
  • Lecturer: Lucian Carata
  • Booktitle: Proceedings of the 27th Spring Conference on Computer Graphics
  • Conference date: 27. April 2011 – 30. April 2011
  • Pages: 1 – 8

Abstract

Technical developments in neurobiology have reached a point where the acquisition of high resolution images representing individual neurons and synapses becomes possible. For this, the brain tissue samples are sliced using a diamond knife and imaged with electron-microscopy (EM). However, the technique achieves a low resolution in the cutting direction, due to limitations of the mechanical process, making a direct visualization of a dataset difficult. We aim to increase the depth resolution of the volume by adding new image slices interpolated from the existing ones, without requiring modifications to the EM image-capturing method. As classical interpolation methods do not provide satisfactory results on this type of data, the current paper proposes a re-framing of the problem in terms of motion volumes, considering the depth axis as a temporal axis. An optical flow method is adapted to estimate the motion vectors of pixels in the EM images, and this information is used to compute and insert multiple new images at certain depths in the volume. We evaluate the visualization results in comparison with interpolation methods currently used on EM data, transforming the highly anisotropic original dataset into a dataset with a larger depth resolution. The interpolation based on optical flow better reveals neurite structures with realistic undistorted shapes, and helps to easier map neuronal connections.

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BibTeX

@inproceedings{Carata_2011_IVE,
  title =      "Improving the Visualization of Electron-Microscopy Data
               Through Optical Flow Interpolation",
  author =     "Lucian Carata and Dan Shao and Markus Hadwiger and Eduard
               Gr\"{o}ller",
  year =       "2011",
  abstract =   "Technical developments in neurobiology have reached a point
               where the acquisition of high resolution images representing
               individual neurons and synapses becomes possible. For this,
               the brain tissue samples are sliced using a diamond knife
               and imaged with electron-microscopy (EM). However, the
               technique achieves a low resolution in the cutting
               direction, due to limitations of the mechanical process,
               making a direct visualization of a dataset difficult. We aim
               to increase the depth resolution of the volume by adding new
               image slices interpolated from the existing ones, without
               requiring modifications to the EM image-capturing method. As
               classical interpolation methods do not provide satisfactory
               results on this type of data, the current paper proposes a
               re-framing of the problem in terms of motion volumes,
               considering the depth axis as a temporal axis. An optical
               flow method is adapted to estimate the motion vectors of
               pixels in the EM images, and this information is used to
               compute and insert multiple new images at certain depths in
               the volume. We evaluate the visualization results in
               comparison with interpolation methods currently used on EM
               data, transforming the highly anisotropic original dataset
               into a dataset with a larger depth resolution. The
               interpolation based on optical flow better reveals neurite
               structures with realistic undistorted shapes, and helps to
               easier map neuronal connections.",
  month =      apr,
  organization = "Spring Conference on Computer Graphics",
  location =   "Vini\v{c}n\'{e}, Slovak Republic",
  booktitle =  "Proceedings of the 27th Spring Conference on Computer
               Graphics",
  pages =      "1--8",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2011/Carata_2011_IVE/",
}