Biomedical Engineering Reference
In-Depth Information
CNRS Vs for each ROI's in the validated frames
25
r(+) (Blood)
b(*) (Intima)
g(s) Media)
m(c) (Adventitia)
y(d) (Average)
20
15
10
5
0
0
2
6
8
Validated frames
14
16
18
4
10
12
20
Figure 1.45:
CNRS values for each ROI of 20 manually segmented image
frames.
It is very important to note that the gray-level difference distribution ex-
hibited Gaussian distributions for all regions of interest. Certainly, the syn-
thetic image brightness is an open problem of the image formation model.
The simplest approach is to variate it by modifying the original intensity
I
o
of the ultrasound beam, similar to the offset of the image acquisition
system. Real and simulated gray-level distributions for each region of in-
terest are shown in Figs. 1.48 and 1.49. We can note the great similarity
in the gray-level distributions profile. Figure 1.50 shows the gray-level his-
togram of the different tissues structures that appear in IVUS images. As
expected, it can be seen that the gray-level distributions of different struc-
tures overlap and as a result it is not possible to separate the main regions
of interest in IVUS images, using only the gray-level distributions as image
descriptors.
