DEVELOPMENT AND IMPLEMENTATION OF AN AUTOMATIC COUNTING SYSTEM FOR CR-39 SSTND

Name: Moayyad Mazen Alssabbagh

Matric No.: MGQ120003

Supervisor: Mr. Tan Li Kuo

Co-supervisor: Prof. Kwan-Hoong Ng and Dr. Vincent Phua

UNIVERSITI

M A L A Y A

MEDICAL PHYSICS RESEARCH PROJECT

MGQG6189

INTRODUCTION • The CR-39 solid state passive nuclear track detector is a

popular method to measure charged particle and neutron radiation due to its low cost, robustness, track permanence, and insensitivity to Gamma, X-ray, Beta and Electromagnetic waves.

• Heavy charged particles passing through these passive detectors leave a narrow trail of damage; this damage is visible at modest optical magnification levels.

• Traditional manual counting methods are labor intensive and highly operator dependent.

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CR-39

Damage trails or Tracks

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• The main aim of this research is to develop an affordable automatic CR-39 track counting system.

• Comparing the obtained results from the software with the manual ones.

OBJECTIVES

BACKGROUND AND LITERATURE REVIEW

• CR-39 detectors are constructed from a polyallyl diglycol carbonate (C12H18O7)

• Applications: Radon dosimetry, Personal neutron dosimeter.

• Advantages: inexpensive, insensitive to EM, simple processing method, robust, transparent and can be cut into small pieces.

• Disadvantages: not reusable, counting is time consuming (manual counting), Commercial digital system (expensive)

BACKGROUND AND LITERATURE REVIEW (Cont.)

• The characteristic of tracks: small light spot and uniform shape (circular or elliptical)

• The diameter is affected by:

1. etching conditions (time, temp., concentration … etc.) and

2. The energy of incident particles

Artefacts

Tracks

BACKGROUND AND LITERATURE REVIEW (Cont.)

• Most track-reading systems use:

1. conventional optical microscopes.

2. high resolution charged couple device (CCD) camera to capture the magnified

picture.

• Commercial software packages used for track counting, such as:

• Image-Pro

• Free software as Image-J

• Monte Carlo simulation

• Others used MATLAB® (Patiris, Blekas, & Ioannides, 2007) (Ahn & Lee, 2005; Puglies, Sciani, Stanojev

Pereira, & Pugliesi, 2007) (Dwaikat, et al., 2010) (Zylstra, et al., 2012).

METHODOLOGY

EQUIPMENT USED

• Traditional Microscope

• Full Digital Microscope

• Stage micro-ruler microscope slide

• CR-39 detectors.

• Ra-226 with activity of 122KBq (AECS)

• Chemical solution (NaOH)

• MatLab software v. R2009a

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METHODOLOGY (Cont.)

• A set of CR-39 detectors with dimensions of 1.5 cm x 1.3 cm were exposed to Ra-226 for different time periods (1, 2, 4, 8 and 12 hours).

• 6 M of NaOH solution at a 70 ᵒC over 7 hours used for etching process.

• Two Microscopes were used to capture the images of the detectors:

• The first one was a traditional light microscope with a digital camera connected to the eye piece. (0.3 MP)

• The second microscope was a full digital one with an LCD monitor with an area of 3.5” which acts as a 10x eyepiece. (2 MP).

• The same magnification (40x) was used for both microscopes.

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METHODOLOGY (Cont.)

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• Manual and Automatic counting were performed for

both images from old and new microscope.

• A comparison between manual and automated

counting is performed.

RESULTS

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Manual counting.: Traditional microscope and the Digital Microscope

20 scenes have been captured from each detector. Manual counting has been done

and the average was calculated.

(Traditional: 0.7 mm x 0.55 mm) (Digital: 1 mm x 1.3 mm)

RESULTS (Cont.)

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Automatic counting.: Traditional microscope and the Digital Microscope

Automatic counting has been done for the 20 scenes of each detector and the

average was calculated.

RESULTS (Cont.)

Manual counting.: Traditional microscope and the Digital Microscope

Table 1: The difference of reading for both manual and automatic counting (first & second

microscopes)

First microscope Second microscope

Exp. time

(hr)

Radon Con.

kBq.h/m3

Manual

counting

Auto.

counting

Difference

in reading

Manual

counting

Auto.

counting

Difference

in reading

1 170 973 850 14.9% 516 550 6.6%

2 340 1671 1565 6.3% 1094 1124 2.7%

4 680 3052 2750 9.9% 2976 2927 1.6%

8 1360 5434 3789 30.3% 5857 5857 0.0%

13 2210 9157 6144 32.9% 10713 10602 1.0%

RESULTS (Cont.)

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Calibration curves for manual counting:

Traditional microscope and the Digital Microscope

973

1671

3052

5434

9157 y = 4.1467x

R² = 0.9946

0.00

1000.00

2000.00

3000.00

4000.00

5000.00

6000.00

7000.00

8000.00

9000.00

10000.00

0 500 1000 1500 2000 2500

De

nsit

y (T

r/cm

2)

Radon Exp. (KBq.hr/m3)

Calibration curve for manual counting

(Traditional Microscope)

516 1094

2976

5857

10713 y = 4.6491x

R² = 0.9892

0.00

2000.00

4000.00

6000.00

8000.00

10000.00

12000.00

0 500 1000 1500 2000 2500D

en

sit

y (T

r/cm

2)

Radon Cons. (KBq.hr/cm3)

Calibration curve of manual counting

(New Microscope)

RESULTS (Cont.)

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Calibration curves for Automatic counting:

Traditional microscope and the Digital Microscope

868

1434

2421

3789

6144 y = 2.8629x R² = 0.9648

0.00

1000.00

2000.00

3000.00

4000.00

5000.00

6000.00

7000.00

0 500 1000 1500 2000 2500

De

nsi

ty (

Tr/c

m2

)

Radon Exp. (KBq.hr/cm3)

Calibration curve for automatic counting (Traditional Microscope)

550 1124

2927

5857

10602 y = 4.6133x R² = 0.9907

0.00

2000.00

4000.00

6000.00

8000.00

10000.00

12000.00

0 500 1000 1500 2000 2500D

en

sity

(Tr

/cm

2)

Radon Cons. (KBq.hr/cm3)

Calibration curve of Automatic Counting (New Microscope)

DISCUSSION

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Elliptical

tracks

Circle

tracks

Bubbles

Defects

De-noising the image means to remove the scratches, bubbles and small dots that are caused by the camera or the detector itself. To achieve a clear and acceptable image, the program depends on three Steps: 1. Binary threshold 2. Size Threshold 3. Circularity Threshold

DISCUSSION (Cont.)

Binary

• The tracks are usually having lower brightness than the defects (more dark). The image is converted to binary image (Black and white) All pixels having an illumination greater than the threshold value replaced with the value of 1 while the other pixels with the value of 0 .

• Clearness of the images affected by the illumination number of tracks counted .

• The user has to chose the binary threshold.

Origin image Traditional Microscope Digital Microscope

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DISCUSSION (Cont.)

Size threshold

The tracks either have circular or elliptical shapes.

All objects with less than the pixel threshold were removed. (26 pixel minimum, 201 pixel maximum)

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DISCUSSION (Cont.)

Circularity

Circularity threshold was settled to 0.75 - 1 (practically) this is sufficient for the detection of circular and elliptical tracks, and objects having values less than this threshold will not be considered as tracks.

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The uncounted objects were

surrounded by white lines

𝑅 = 4𝜋. 𝐴𝑟𝑒𝑎

𝑃𝑒𝑟𝑖𝑚𝑒𝑡𝑒𝑟2

LIMITATION

• The uniformity of illumination is very important to reduce the graded black shadows on the image edges

• The system currently lacks features such as counting overlapping tracks and calculating their average size to estimate the average energy

• The binary threshold value entered manually by the user and still observer dependent

FUTURE WORK

• One of the suggested methods to count the overlapping tracks is to divide the size of the overlapped tracks by the average size of individual track. This method need to be tested for various overlapping tracks from different detectors and different particles’ energies

• An algorithm should be developed to calculate the binary threshold value automatically.

• Enhance the system to detect tracks under the graded black edges on image.

CONCLUSION

• By using MATLAB® software, an automatic system that can count the tracks on the CR-39 was developed.

• The system is highly dependent on image clearness. Despite this, the system showed the ability to count the tracks on different resolutions (0.3 Megapixel and 2 Megapixel )

• A good ability to find and count elliptical tracks .

• The system takes less than one minute for track counting per detector .

Finally

A new set of CR-39 has exposed

to a photon beam in LINAC unit to

detect the neutron activation

when using megavoltage of 10MV Optically Stimulated Luminescence (OSL)

Thank You

Questions

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