Descriptionx

ranchocucamongabrrrΤεχνίτη Νοημοσύνη και Ρομποτική

6 Νοε 2013 (πριν από 3 χρόνια και 8 μήνες)

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Technical Description


1. Description of the system


The additional system is a portable system which can process the ultrasound diagnostic images
by just plug to the video output port of the ultrasound diagnostic machine. In addition,
measurement of
the parameter
distances can be done also within the system either manually or
automatically.

The system is designed to have a user friendly Graphical User Interface (GUI). This user friendly
GUI makes the system easy to operate. There are few buttons with

operation labels. By just one
click on the desired operation, the operation can be done.

The developed system (
Sonoimprometer
) consists of two main parts, hardware and software
part. The hardware part is mainly the system configuration which includes the

processor and the
video grabber. On the other hand, the software part is mainly on image enhancement,
measurement and GUI.


2. System Configuration


Figure 1 shows the block diagram of the developed system and Figure 2 shows the electronic
block diagram f
or developed system. The system is connected through multi purposes connectors
to the video port of ultrasound machine. The processor is used to improve the image quality, to
do some measurement and to produce the improved images or result on a separate di
splay.The
main of the system is the processor where the image processing algorithm is implemented here.
Besides, it is the main controller of the whole system. The display for the additional system is
also controlled by the processor.



Figure 1
: Block di
agram of developed system.



Figure 2
: Electronic block diagram for developed system



3. Software

The software part consists of image processing
unit and
measurement

unit for i
mage
quality
parameters and

user
-
friendly GUI.


a.


Image Processing Algorithm

The main purpose of image processing is to enhance the ultrasound image so that ultrasound
image will be easier to read. Several image processing techniques are used to enhance the image.
This includes image merging to retain some details of the ultrasound

image, scaling to smooth
the images and finally some simple mathematical operations are done to control the in
tensity of
the image. Figure 3

shows the flow of the applied image processing techniques.




Figure 3
: Flow of i
mage processing algorithm.


For image enhancement, the main purpose is to enhance the contrast so that the object being
scanned will be clearer or obvious. In order to enhance the contrast, simple mathematical
operations are done. Firstly, multiplication i
s done to make the higher value pixels getting higher
value. In other hand, this makes bright pixels getting brighter but dark pixels stay dark. The
difference between dark and bright pixels will be obviously seen. Secondly, deduction is being
done to cont
rol the intensity of the image so that the bright pixels will not getting too bright and
look unreal.






b.

Measurement




Figure 4
: Flow of automatic measurement.


The developed system is designed to be
able to do measurement automatically and manually.
Firstly, in order to do measurement, calibration has to be done. User will be prompted to done
calibration by enter a desired calibration distance value. Then the user can shows the calibration
distance by

clicking two points on the picture. The distance is calculated.

For all measurement, the program will first crop the region that the objects that to be measured
may take place. Then, the enhancement on the crop region is done

before the edge detection.

T
he result of applying an edge detector to an image may lead to a set of connected curves that
indicate the boundaries of objects, the boundaries of surface markings as well curves that
correspond to discontinuities in surface orientation. Thus, applying an

edge detector to an image
may significantly reduce the amount of data to be processed and may therefore filter out
information that may be regarded as less relevant, while preserving the important structural
properties of an image.

For all the objects in
the cropped region, the areas of those objects are calculated in pixels. The
object with the highest value of area is the target that we needed. Therefore, the objects to be
measured can be identified. The other objects in the region are considered as nois
e and will be
ignored during any measurement. In order to get a better result, average calculation will be done
and the result will be displayed at the GUI of this program.



Detailed description

An automatic measurement and enhancement system (Sonoimprome
ter) for low cost ultrasound
mechine has been developed. The system consists of low cost hardware and software. The
hardware consist of video grabber (self programming) high speed processor (general processor
1.2 GHz), multifunction and small size main boa
rd (micro ATX, multi I/O), high capacity and
small size memory (RAM 1GB), small size switching power supply and heat thermal
management (fan and stainless steel heat sink). The image quality enhancement and
measurement is done using software. The main fun
ction function of the developed software is
automatic measurement for :

1) Dead zone


2) Distance accuracy: horizontal and vertical distance


3) Resolution: axial and lateral resolution


4)

Uniformity


5)

Penetration depth


6)

High scatter diameter

The
system is able to enhance the image quality of low cost ultrasound machine. Besides, the
software are developed with user friendly GUI. A test has been done to measure the image of
low cost ultrasound machines and the result shows that most of the low cost

ultrasound machine
has low image quality. The system is suitable to monitor all of the ultrasound machines which
consist of video port and proposed to be used as part of routine maintenance in clinics and
hospitals.


Detail description about how the Sonoi
mprometer works.

1.

Grab the phantom images from ultrasound machine and save the images.

2.

Display the image on the GUI.

3.

Run the image enhancement process.




1

2

3

4.

Image enhancement process

a.

Speckle Reducing Anisotropic Diffusion

5.

Compare the
image before enhance and after enhance.

6.

Save the after enhance image and back to the front page of the GUI.




4

5

6

7.

Click the ‘PARAMETER
’ button to run the auto measurement of all the parameters for
the image before enhance and after
enhance.

8.

Manual measurements for the image before enhance.

9.

Auto measurements for the image before enhance.

10.

Results of the parameters for the image before enhance.

11.

Open the image after enhance.



12.

Run the same procedure

as shown in steps 8


10 in Enhanced Image.

13.

Click the ‘REPORT’ button to open the results in table format.

14.

Report as show below.


9

8

10

11