Locally Adaptive Marching Cubes through Iso-value Variation

Michael Glanznig, Muhammad Muddassir Malik, Meister Eduard Gröller
Locally Adaptive Marching Cubes through Iso-value Variation
In Proceedings of the International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, pages 33-40. February 2009.
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Abstract

We present a locally adaptive marching cubes algorithm. It is a modification of the marching cubes algorithm where instead of a global iso-value each grid point has its own iso-value. This defines an iso-value field, which modifies the case identification process in the algorithm. The marching cubes algorithm uses linear interpolation to compute intersections of the surface with the cell edges. Our modification computes the intersection of two general line segments, because there is no longer a constant iso-value at each cube vertex. An iso-value field enables the algorithm to correct biases within the dataset like low frequency noise, contrast drifts, local density variations and other artefacts introduced by the measurement process. It can also be used for blending between different isosurfaces (e.g., skin, veins and bone in a medical dataset).

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@inproceedings{glanznig-2009-LAMC,
  title =      "Locally Adaptive Marching Cubes through Iso-value Variation",
  author =     "Michael Glanznig and Muhammad Muddassir Malik and Meister
               Eduard Gr{\"o}ller",
  year =       "2009",
  abstract =   "We present a locally adaptive marching cubes algorithm. It
               is a modification of the marching cubes algorithm where
               instead of a global iso-value each grid point has its own
               iso-value. This defines an iso-value field, which modifies
               the case identification process in the algorithm. The
               marching cubes algorithm uses linear interpolation to
               compute intersections of the surface with the cell edges.
               Our modification computes the intersection of two general
               line segments, because there is no longer a constant
               iso-value at each cube vertex. An iso-value field enables
               the algorithm to correct biases within the dataset like low
               frequency noise, contrast drifts, local density variations
               and other artefacts introduced by the measurement process.
               It can also be used for blending between different
               isosurfaces (e.g., skin, veins and bone in a medical
               dataset).",
  pages =      "33--40",
  month =      feb,
  booktitle =  "Proceedings of the International Conference in Central
               Europe on Computer Graphics, Visualization and Computer
               Vision",
  editor =     "Vaclav Skala",
  isbn =       "978-80-86943-93-0",
  location =   "Plzen, Tschechien",
  keywords =   "isosurface correction, iso-value field, contouring, marching
               cubes, blending between isosurfaces",
  URL =        "http://www.cg.tuwien.ac.at/research/publications/2009/glanznig-2009-LAMC/",
}