Biomedical Engineering Reference
In-Depth Information
Table 8.1:
Parameters for processing example datasets
Dataset
Initialization
Surface Fitting
Dendrite
1. Gaussian blur
σ
=
0
.
5
1. Edge fitting:
σ
=
0
.
75, threshold
=
6,
β
=
0
.
1
2. Threshold:
I
<
127
2. Gradient magnitude fitting:
σ
=
0
.
5,
β
=
1
.
0
3. Fill isolated holes
4. Morphology:
O
0
.
5
◦
C
1
.
5
Mouse
1. Gaussian blur
0
5
1. Edge fitting:
0
75, threshold = 20,
2
σ
=
.
σ
=
.
β
=
2. Threshold:
I
3,
I
60
2. Gradient magnitude fitting:
0
5,
16
0
>
<
σ
=
.
β
=
.
3. Fill isolated holes
4. Morphology:
O
2
.
0
◦
C
3
.
0
Frog
1. Interactive
1. Gradient magnitude fitting:
σ
=
1
.
25,
β
=
1
.
0
The top right image (hour 16) demonstrates the expansion of the blastocoel
and the development of the blastoporal lip in red. In the bottom left image (hour
20) the blastoporal lip has collapsed, the blastocoel has contracted, and the
archenteron in green has developed. In the bottom right image (hour 30) the
blastocoel has collapsed and only the archenteron is present. For this dataset
it was difficult to isolate structures only based on their voxel values. We there-
fore used our interactive techniques to isolate (during initialization) most of the
structures in the frog embryo samples.
Table 8.1 describes for each dataset the specific techniques and parameters
we used for the results in this section. These parameters were obtained by first
making a sensible guess based on the contrasts and sizes of features in the data
and then using trial and error to obtain acceptable results. Each dataset was
processed between four and eight times to achieve these results. More tuning
could improve things further, and once these parameters are set, they work
moderately well for similar modalities with similar subjects. The method is it-
erative, but the update times are proportional to the surface area. On an SGI
180 MHz MIPS 10000 machine, the smaller mouse MR dataset required approx-
imately 10 min of CPU time, and the dendrite dataset ran for approximately 45
min. Most of this time was spent in the initialization (which requires several
complete passes through the data) and in the edge detection. The frog embryo
datasets needed only a few minutes of processing time, because they did not
require computational initialization and are significantly smaller than the other
example datatsets.
