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Abstract
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In general three-dimensional segmentation algorithms assume
objects to have connected homogeneous regions. However in some
cases objects are defined by a fuzzy boundary surface and consist
of an inhomogeneous internal structure. In the following a new
three-dimensional segmentation technique exploiting the contour
detection capabilities of live-wire is proposed: The algorithm
consists of two basic steps. First contours are outlined by the
user on a small number of planar cross-sections through the object
using live-wire. Second the traced contours are used for
reconstructing the object surface automatically in each slice
using live-wire again. This user-friendly segmentation algorithm
is independent from object topology as the topology is implicitly
defined during the reconstruction process.
Keywords: Segmentation, Live-wire.
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Figures in the paper
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Figure 1:
The user traces the object boundary of the tooth dataset
in each orthogonal cross-section. The connectivity points are
depicted by black dots.
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Figure 2:
Three-dimensional display of the cross-sections with
outlines (left), with the reconstructed surface (middle) and the
reconstructed surface (right).
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Figure 3:
Outlines of two cross-sections may have points in
common. These connectivity points are on the intersection line of
two cross-sections.
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Figure 4:
The slice is split into a number of convex polygons by
intersecting cross-sections (left) and its connectivity graph
(right). Letters indicate polygons and numbers indicate outline
points.
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Figure 5:
This figure shows a case where an invalid
intersection occurs. Thick lines mean inside. Left: Two
intersecting cross-sections, where an inside line fragment
intersects an outside fragment. Right: The connectivity
graph of this case.
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Figure 6:
According to Figure 5 two different
modifications are possible, depending on the outline point closer
to the intersection point. This modification turns an
invalid case into a valid case. Left: Point 1 closer
to the invalid intersection point. Right: Point 2 closer to the
intersection point.
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Figure 7:
This figure shows the possible succeeding edges indicated
by arrows pointing away from W.
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Figure 8:
The flow chart of the segmentation process described in section 3 (left side) and 4 (right side).
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Figure 9:
Segmented right leg bones seen from the back applying
thresholding at 386 Hu (top), region growing (middle), the new
method (bottom).
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Figure 10:
Figure 9: Coronal MIP of a CTA dataset. The mask for removing the
bones was generated by thresholding (top), region growing
(middle), the new method (bottom).
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BibTeX Entry
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@InProceedings{Knapp:2003:SAT,
author = {Michael Knapp and Armin Karnitsar and Eduard Gr\"oller},
title = {Semi-Automatic Topology Independent Contour-Based 2 1/2 D Segmentation Using Live-Wire},
booktitle = {Proceedings of WSCG},
year = {2004},
pages = {???--???},
}
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