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TRIPLE FEATURES OF ULTRASONIC IMAGE RECOGNITION1
N.G. Fedotov2, L.A. Shul’ga2, A.S. Kol’chugin2, O.A. Smol’kin2, S.V. Romanov2
2
Penza State University, 40th Krasnaya St., Penza, 440026 Russia, phone +7 8412 368056,
[email protected]
Ultrasonic images recognition problem aimed at thyroid cancer diagnostics sensibility
increasing is considered. Measurement of objects geometrical characteristics on
ultrasonic images, based on stochastic geometry methods - trace-transformation and it
based triple features formed is described.
Introduction
The basic method for screening of thyroid
gland diseases is ultrasonic examination. The
purposes of this examination are a detection of
tumours and definition of theirs characteristics.
The expert carries out the given procedure and
the results are defined by his or her
qualification and experience.
Heterogeneity and complex structure is
characteristic for images of ultrasonic
examination. Algorithms of preprocessing of
images on the basis of a method
morphological grayscale reconstruction have
been applied to simplification of procedure of
recognition. Application of this algorithm has
allowed to allocate tumours in a thyroid gland
for their subsequent analysis.
Calculating of the triple feature
The main geometrical characteristics tumors
are: the size, the form and border. For
definition of the given parameters it is offered
to use methods of stochastic geometry - tracetransformation. The basis of this method is
scanning the image the determined lattice. The
scanning result is trace transform or trace
matrix. With help of subsequent trace matrix
processing the three functionals composition
view triple features are form.
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1
Support of the grant INTAS, Ref. No. 04-77-7036.
Let F x, y  – function of representation on the
plane x, y  .
We fix on this plane scanning line l  ,  , t  ,
which made using normal coordinates  and
:
x cos  y cos   , parameter t assign the
point on the straight line.
Functionals  , P and T are bounded with
normal coordinates  ,  and current
coordinate t correspondently.
We fix the function of these two arguments
g  ,    T F  l  ,  , t  as the result of
action of functional T , under the stipulation
that, values of variable  and  are constant.
As a result of functional T we have matrix,
the elements of matrix are values
t ij  T F  l  j ,  i , t  , the parameters of
scanning line are  and  , determine the
position of this value in the matrix. We’ll
name this matrix as trace-matrix. The next
computation of the feature is in consistent
columns processing with the help of functional
P , and then using functional  .
So the feature calculated like consistent
composition
of
three
functional
П F   T  P  F  l  ,  , t .
The Measurement of the tumor sizes
As the sizes of infected formations present the
maximal extent of object in any measurement
300
(we shall name its length) and the maximal
extent of object in perpendicular to length a
direction (we shall name its width).
If we take functional T as a long of the bigger
cut off section of straight line l  ,  , t  in this
object, and P and  - are upper bounds of
the value, so we can get the maximum
diameter of object (length). We know the
value of this parameter  k for this feature, and
we analyze only row with parameter
   k  90  in the matrix and use the same
functional P we can get the width of the
object.
Fig. 3. Tumor has clear border
Fig. 4. Tumor has unclear border
The definition of the shape of tumor
While carrying out of ultrasonic examination
the shape of infected formations in a thyroid
gland is characterized as regular (Fig. 1) or
irregular (Fig. 2). In the general case we can
name regular shape, which is look like an
ellipse.
We’ll take the long of the bigger cut off of line
section l  ,  , t  as functional T . Functional
P is a value of fluctuation of t ij , and  is
average value. Received feature will be
describing the borders.
Conclusion
Fig. 1. Tumor has regular shape
Thus, carried out research has shown the
effectiveness of application of stochastic
geometry methods for definition of tumor
characteristics in a thyroid gland. The
utilization of trace-features allows to raise
reliability of our dimension, defining the set
characteristic, using various functionals.
References
Fig. 2. Tumor has irregular shape
The function of quantity of point of
intersection in the line l  ,  , t  is functional
T , P and  they are average values. So, the
feature we got will be numerical characteristic
of the object. So if value closed to 2, an object
has regular shape, if more than 2 – has
irregular shape.
Characteristic of the border of tumor
The borders are considered as clear (Fig. 3) or
unclear (Fig. 4).
1. N.G. Fedotov. Stochastic geometry methods in
pattern recognition. Moscow.: Radio i svyaz’, 1990.
(in Russian).
2. N.G. Fedotov, L.A. Shulga, A.V. Moiseev.
Recognition features and image preprocessing
theory based on stochastic geometry //
Izmeritel’naya tekhnika. – 2005. – No.8. - P. 8-13.
(in Russian).