Moment Curves

Daniel Patel, Martin Haidacher, Jean-Paul Balabanian , M. Eduard Gröller

INPROCEEDINGS, Proceedings of the IEEE Pacific Visualization Symposium 2009, April, 2009

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Abstract

We define a transfer function based on the first and second statistical moments. We consider the evolution of the mean and variance with respect to a growing neighborhood around a voxel. This evolution defines a curve in 3D for which we identify important trends and project it back to 2D. The resulting 2D projection can be brushed for easy and robust classification of materials and material borders. The transfer function is applied to both CT and MR data.

Published

Proceedings of the IEEE Pacific Visualization Symposium 2009

• Pages: 201–208
• Location: Beijing, China
• Date: April 2009
• URL: http://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/

Media

BibTeX

@inproceedings{patel09momentCurves,
  author = {Daniel Patel and Martin Haidacher and Jean-Paul Balabanian
            and M. Eduard Gr{\"o}ller},
  title = {Moment Curves},
  year = {2009},
  booktitle = {Proceedings of the IEEE Pacific Visualization Symposium 2009},
  pages = {201--208},


  location = {Beijing, China},
  abstract = {We define a transfer function based on the first and second statistical
	moments. We consider the evolution of the mean and variance with
	respect to a growing neighborhood around a voxel. This evolution
	defines a curve in 3D for which we identify important trends and

	for easy and robust classification of materials and material borders.
	The transfer function is applied to both CT and MR data.},
  month = {April},
  URL = {http://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/}
}