Isosurface Extraction Techniques for Web-based Volume Visualization
The reconstruction of isosurfaces from scalar volume data has positioned
itself as a fundamental visualization technique in many different applications.
But the dramatically increasing size of volumetric data sets often prohibits
the handling of these models on affordable low-end single processor architectures.
Distributed client-server systems integrating high-bandwidth transmission
channels and Web-based visualization tools are one alternative to attack
this particular problem, but therefore new approaches to reduce the load
of numerical processing and the number of generated primitives are required.
In this paper we outline different scenarios for distributed isosurface
reconstruction from large-scale volumetric data sets. We demonstrate how
to directly generate stripped surface representations and we introduce
adaptive and hierarchical concepts to minimize the number of vertices that
have to be reconstructed, transmitted and rendered. Furthermore,
we propose a novel computation scheme, which allows the user to flexibly
exploit locally available resources. The proposed algorithms have
been merged together in order to build a platform-independent Web-based
application. Extensive use of VRML and Java OpenGL-bindings allows for
the exploration of large-scale volume data quite efficiently.
Advanced isosurface representation
1. Reconstructing stripped surfaces
One way to compress a triangle mesh is to reorganize multiple triangles
into one triangle strip. For each vertex presented after the first two
vertices one triangle is defined. Obviously, organizing triangle meshes
as strip sets considerably reduces the number of vertices needed to represent
the mesh and thus the number of operations necessary to render the mesh.
By providing a method that is capable to directly reconstruct stripped
isosurfaces we simultaneously address the problem to reduce the load on
the transmission channel and to optimize the rendering performance.
Images
Stripped isosurfaces: cell stripped, single direction
stripped, multi-direction stripped
multi-direction stripped isosurface of an MRI scan
Movies(MPEG)
Transferring and visualizing strips at different
levels of detail (3.9MB) - OpenGL bindings visualization
2. Level-of-detail isosurface reconstruction
Although in the previous approach the number of primitives was reduced
in a quite efficient way by reorganizing the geometric representation,
usually interactivity cannot be achieved particularly for large-scale data
sets. In general, we believe that in the proposed environment interactive
frame rates can only be achieved by taking advantage of the hierarchical
nature of multi-resolution techniques to effectively decimate the number
of primitives needed to represent the surface.
Adaptive on-the-fly reconstruction and rendering is performed from
a hierarchical octree representation thus allowing the user to interactively
browse through all possible isosurfaces.
In order to allow for the exploration of even the highest resolution
data sets the user can manually select a region of interest in which the
surface is reconstructed at the finest level. Outside of this region the
surface is reconstructed at increasingly coarser resolution. In this way
it is possible to adaptively select the size and the number of details
that should be reconstructed at the same time achieving sufficient frame
rates for interactive navigation.
Images
focus point (red ball) with small and big radius
focus point (red ball)showing left part of the isosurface with increased
level-of-detail
Movies
Moving the focus point on the surface of a head (6.9MB)
- VRML visualization
Distributed isosurface reconstruction
We can exploit locally available computing power of the client system to
reduce the idle times and to balance the load on all involved units more
equally. Therefore we developed a distributed computation scheme which
allows vertex positions to be calculated on the client.
Images
CT scan dataset (512x512x120): view onto the eyeballs
(aneurysm marked by focus) , aneurysm shown with high level-of-detail
Movies
CT dataset (512x512x106): Moving the focus point
on the cerebral artery to an aneurysm (berry-like blister of the cerebral
artery) (6.9MB, 13.5MB)
References
R. Westermann, L. Kobbelt, T. Ertl
Real-time
Exploration of Regular Volume Data by Adaptive Reconstruction of Iso-Surfaces
The Visual Computer 1998
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