![](bg3.png)
which are not easy to visualize without explicit
segmentation of structures of interest.
The importance of clusters is utilized in gradient
peeling with importance. In other words, gradient
peeling with importance will only be triggered on
clusters with importance factors greater than the
user-defined threshold.
Instead of peeling off opaque material, gradient
peeling is design to peel off translucent material and
boundary regions. This is based on an observation
that the boundaries in a volume data set contribute
most to the accumulated value of gradients. Hence
gradient peeling which accumulates and measures
the gradients will has better performance on peeling
off boundary regions than opacity peeling which
accumulates and measures opacity values.
The mechanism of gradient peeling is very
similar to that of opacity peeling. That is to peel off
layers of material with certain accumulated gradient
magnitude and only to start new layers in blank
regions. Two thresholds are used for peeling, the
accumulated threshold and the current sampled
threshold. When the accumulated value reaches the
accumulated threshold and the sampled value of
current voxel is less than the sample threshold, a
layer will be peeled off.
4 RESULTS AND DISCUSSION
For the convenience of comparison, we implemented
our importance-driven techniques with a simple
scalar value (1D) transfer function, and put the
rendering results with and without the importance-
driven techniques in this section.
The importance-driven techniques allow users to
visualize the clusters of their interests.
Figure 3
and
Figure 4
are rendered from the same nucleon dataset
in
Figure 1
. In
Figure 3
, the exterior of the nucleon is
removed, because the importance of the exterior of
the nucleon is set to zero. On the contrary, in
Figure 4
,
the importance of interior of the nucleon is set to
zero, so that it is invisible in the image. These two
images show the ability of the importance-driven
techniques to rendered specific parts of the dataset
by assigning importance to clusters.
The importance-driven techniques are capable to
reveal inner structures.
Figure 5
is a foot dataset
rendered with the 1D transfer function, and
Figure 6
is the same dataset rendered with the 1D transfer
function and the importance-driven techniques. In
Figure 6
, the exterior of the foot (skin and muscles)
are completely removed, and the articulations and
the phalanges are exposed entirely. Similarly, in the
result of the VisMale dataset (Roettger, 2006)
rendered with the 1D transfer function (
Figure 7
), the
outside clusters are nearly opaque so that the
visibility of the skull inside is very limited. By
contrast, in the result with importance-driven
techniques (
Figure 8
), the outside clusters, i.e. skin
and muscles, are transparent, and the inside clusters,
i.e. the skull, is clearly visible.
Gradient peeling is better at peeling translucent
material and thin structures than the opacity.
Compare to the results of opacity peeling (
Figure 9
and
Figure 10
), the results of gradient peeling (
Figure
11
and
Figure 12
) have more details of the surface of
the skull. It is more obvious in the second layer than
in the first layer. In
Figure 10
, parts of the surface of
the skull are peeled away entirely, and the skull can
be seen through. This difference is derived from the
thresholds setting in opacity peeling and gradient
peeling. When peeling translucent boundaries of soft
tissues or thin structures, it is difficult to set an
appropriate threshold in opacity peeling, and a slight
adjustment to the thresholds will reflect in a rapid
change in the resulting image. Since the thresholds
in opacity peeling are set on accumulated opacity, it
is more capable in peeling opaque materials than
translucent boundaries, which are of little opacity.
On the other hand, since the thresholds in gradient
peeling are set on accumulated gradients, gradient
peeling is sensitive to the changes of opacity even if
that is translucent, which is usually happen in the
boundaries of soft tissues and thin structures.
Figure 3: The exterior of
the nucleon is removed.
Figure 4: The interior of
the nucleon is removed.
Figure 5: 1D transfer
function.
Figure 6: 1D transfer
function with
importance.
IMPORTANCE-DRIVEN VOLUME RENDERING AND GRADIENT PEELING
213