Improving the visualization of electron-microscopy data through optical flow interpolation
Type
Conference PaperKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionComputer Science Program
Visual Computing Center (VCC)
Date
2013Permanent link to this record
http://hdl.handle.net/10754/564658
Metadata
Show full item recordAbstract
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. © 2011 ACM.Citation
Carata, L., Shao, D., Hadwiger, M., & Groeller, E. (2013). Improving the visualization of electron-microscopy data through optical flow interpolation. Proceedings of the 27th Spring Conference on Computer Graphics - SCCG ’11. doi:10.1145/2461217.2461238Conference/Event name
27th Spring Conference on Computer Graphics, SCCG 2011ISBN
9781450319782ae974a485f413a2113503eed53cd6c53
10.1145/2461217.2461238