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Brain structure visualization using spectral fiber clustering

Published: 30 July 2006 Publication History

Abstract

The visualization of human brain structure is an important new challenge in the area of computer graphics. We present a novel algorithm that allows for visualizing white matter fiber tracts in realtime. Related structure is grouped by our spectral clustering method very efficiently and curvature and spatial depth of the fibers are accentuated by new GPU-based illustrative rendering techniques. Our fiber clustering results are much more accurate and comprehensible than that obtained by previous feature space methods.

References

[1]
Enders, R, Sauber, N., Merhof, D., Hastreiter, P., Nimsky, C., and Stamminger, M. 2005. Visualization of white matter tracts with wrapped streamlines. In IEEE Visualization 2005, 51--58.
[2]
Ibanez, L., Aylward, S., and Kindlmann, G. 2005. Hot topics in 3D medical visualization. In SIGGRAPH 2005 Tutorial.
[3]
Pauly, M., and Gross, M. 2001. Spectral processing of point-sampled geometry. In SIGGRAPH 2001, 379--386.
[4]
Strothotte, T., and Schlechtweg, S. 2002. Non-Photorealistic Computer Graphics: Modeling, Rendering, and Animation. Morgan Kaufmann Publishers, San Francisco.

Cited By

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  • (2016)A Survey of Perceptually Motivated 3D Visualization of Medical Image DataComputer Graphics Forum10.5555/3071534.307158735:3(501-525)Online publication date: 1-Jun-2016
  • (2016)A Survey of Perceptually Motivated 3D Visualization of Medical Image DataComputer Graphics Forum10.1111/cgf.1292735:3(501-525)Online publication date: 4-Jul-2016
  • (2015)Exploration of the Brain’s White Matter Structure through Visual Abstraction and Multi-Scale Local Fiber Tract ContractionIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2015.240332321:7(808-821)Online publication date: 1-Jul-2015
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cover image ACM Conferences
SIGGRAPH '06: ACM SIGGRAPH 2006 Research posters
July 2006
217 pages
ISBN:1595933646
DOI:10.1145/1179622
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 July 2006

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Cited By

View all
  • (2016)A Survey of Perceptually Motivated 3D Visualization of Medical Image DataComputer Graphics Forum10.5555/3071534.307158735:3(501-525)Online publication date: 1-Jun-2016
  • (2016)A Survey of Perceptually Motivated 3D Visualization of Medical Image DataComputer Graphics Forum10.1111/cgf.1292735:3(501-525)Online publication date: 4-Jul-2016
  • (2015)Exploration of the Brain’s White Matter Structure through Visual Abstraction and Multi-Scale Local Fiber Tract ContractionIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2015.240332321:7(808-821)Online publication date: 1-Jul-2015
  • (2015)A Survey of Illustrative Visualization Techniques for Diffusion-Weighted MRI TractographyVisualization and Processing of Higher Order Descriptors for Multi-Valued Data10.1007/978-3-319-15090-1_12(235-256)Online publication date: 2015
  • (2012)A Neuron Membrane Mesh Representation for Visualization of Electrophysiological SimulationsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2011.5518:2(214-227)Online publication date: 1-Feb-2012
  • (2009)Depth-Dependent HalosIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2009.13815:6(1299-1306)Online publication date: 1-Nov-2009

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