Image Processing Reference

In-Depth Information

3.2.2 Segmentation accuracy

To further explain the accuracy of our algorithm, we introduce another area-based evaluation

method then. The area overlap ratio criteria are the most common evaluation criteria in medic-

al images, which are the ratio of overlapped area between the segmented region of VFC Snake

method and the criterion region of ground truth segmented manually. The performance of the

proposed method and the typical VFC Snake method is tested on the successfully detected

mammograms of MIAS by the following equation:

(15)

where
L
is the area segmented by VFC Snake model,
T
is the area of ground truth.
S
L
∩
T
and

S
L
∪
T
are the intersection area and union set area of the two regions, respectively. The average

area overlap ratio and the variance of the segmentation results are shown in
Table 2
. We can

see that the average area overlap ratio of improved method is much higher than the typical

method, and the variance is much lower, that is to say, our auto-segmented results are gen-

erally much more close to the ground truth. It is proved that our approach indeed performs

much more excellent results compared with the typical method.

Table 2

Area Overlap Ratio of Different Methods

Method

Mean (%) Variance (%)

Typical method

76.0151

11.5249

Improved method 90.4073

2.1556

3.2.3 Segmentation similarity

Finally, we introduce a new measure method of medical image segmentation which is based

lected the difference between the region of arithmetic-segmented result and manual-segmen-

ted result, while it could neither reflect the difference nearby the contour nor estimate whether

the arithmetic-segmented curve is bigger or smaller than the ground truth.

mean and standard deviation of the bigger portion, which consist of points from segmented

contour outside the ground truth (segmented manually), and
m
inside
and
σ
inside
are the mean

and standard deviation values of the smaller portion, which are inside.
R
equ
is the radius of a

circle equivalent to the segmented region. Here, the value of
σ
reflects the level of similarity,

the smaller the
σ
value is, the higher similarity level has been reflected.

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