Biomedical Engineering Reference
In-Depth Information
(viii)
Evaluate each pixel in n-label for 270°
0,
I
x
,
y
+
k
if
b
=
n
,
1,
I
x
,
y
+
k
if
b
=
n
,
f
(
x
,
y
)
=
(3.72)
where
k
=
1
→
L
L = maximum number of row -x
(viii)
Evaluate each pixel in n-label for 315°
0,
I
x
+
m
,
y
+
k
if
b
=
n
,
1,
I
x
+
m
,
y
+
k
if
b
=
n
,
f
(
x
,
y
)
=
where
k
=
1
→
L
1
m
=
1
→
L
2
L1 = maximum number of row
−
y
L2 = maximum number of column
−
x
(3.73)
(B) Stopping criteria:
∪
n
=
N
where N = Maximum Label
f
(
x
,
y
)
=
1
(3.74)
(C) Verification of bounded area for n-label
n
−
labelled area
max
y
f
(
x
,
y
)
I
x
,
y
total number of pixels in in
−
label
=
1
non - bounded area, otherwise
max
x
x
bounded area,
if
(3.75)
=
(D) Repeat the process with n
=
n
+
1, where n denotes the label number of pixels
in image.
(E) Fill the pixels belong to bounded area with original value/background value of
pixel intensity of the corresponding coordinate in the image:
I
x
,
y
=
I
x
,
y
(3.76))
The BARNAE algorithm analyzes each of the third group pixel found using
multiple Gaussian model. The result of the analysis determines whether the pixel
is wrongly classified. If the pixel should belong to soft-tissue region, but has been
Search WWH ::
Custom Search