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dc.contributor.authorCarata, Lucian
dc.contributor.authorShao, Dan
dc.contributor.authorHadwiger, Markus
dc.contributor.authorGröeller, Eduard
dc.date.accessioned2015-08-04T07:11:13Z
dc.date.available2015-08-04T07:11:13Z
dc.date.issued2013
dc.identifier.isbn9781450319782
dc.identifier.doi10.1145/2461217.2461238
dc.identifier.urihttp://hdl.handle.net/10754/564658
dc.description.abstractTechnical 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.
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectinterpolation
dc.subjectoptical flow
dc.subjectvolume visualization
dc.titleImproving the visualization of electron-microscopy data through optical flow interpolation
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science Program
dc.contributor.departmentVisual Computing Center (VCC)
dc.identifier.journalProceedings of the 27th Spring Conference on Computer Graphics - SCCG '11
dc.conference.date28 April 2011 through 30 April 2011
dc.conference.name27th Spring Conference on Computer Graphics, SCCG 2011
dc.conference.locationVinicne
dc.contributor.institutionFaculty of Automatic Control and Computer Engineering, Gh. Asachi Technical University of Iasi, Romania
dc.contributor.institutionInstitute of Computer Graphics and Algorithms, Vienna University of Technology, Austria
kaust.personHadwiger, Markus


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