Biomedical Engineering Reference
In-Depth Information
(a)
(b)
Figure 7.15: (a) Example showing an incorrect result. ( b) Anisotropic diffusion
in a preprocessing phase improving final result.
the multiresolution approach is that at the lower resolution, small background
artifacts become less significant relative to the object(s) of interest. Besides, it
avoids the computational cost of using a finer grid resolution to get closer to the
target (see Section 7.4).
The T-surfaces parameters are
γ
=
0
.
01,
k
=
1
.
222, and
c
=
0
.
750. The total
number of evolution is 13. The number of triangular elements is 10 104 for the
highest resolution and the clock time was of the order of 3 min.
Sometimes, even the finest resolution may not be enough to get the correct
result. Figure 7.15(a) pictures such an example.
In this case, we segment an artery from a 155
×
170
×
165 image volume
obtained from the visible human project. The T-surfaces parameters are:
c
=
0
.
75,
k
=
1
.
12,
γ
=
0
.
3, grid resolution is 4
×
4
×
4, and freezing point is set to
10. The result of steps (1)-(6) is pictured in Fig. 7.15(a).
Among the proposals to address this problem (relax the threshold, mathemat-
ical morphology [59], etc.), we tested anisotropic diffusion [52]. The properties
of this method (Section 7.8) enable smoothing within regions in preference to
smoothing across boundaries. Figure 7.15( b) shows the correct result obtained
when preprocessing the image with anisotropic diffusion and then applying steps
(1)-(6).
7.9.3 Out-of-Core Segmentation
In this section, we attempt to experimentally demonstrate our out-of-core seg-
mentation technique. We consider three gray-level data sets and a 3D color image
(Table 7.1).
