Removing spurious signals from glow curves using an optimal Wiener filter

Area of Science:

• Physics
• Dosimetry
• Signal Processing

Background:

• Thermoluminescence dosimetry (TLD) is crucial for radiation dose assessment.
• Spurious signal spikes in TLD glow curves can significantly impact dose evaluation accuracy.
• Current spike detection methods often rely on comparing raw and smoothed glow curves.

Purpose of the Study:

• To develop an improved method for detecting spurious signal spikes in TLD glow curves.
• To enhance the accuracy of dose evaluation by mitigating the effects of signal noise.
• To introduce a robust technique for glow curve quality control.

Main Methods:

• Smoothing of TLD glow curves using an optimal Wiener filter.
• Utilizing Fourier analysis for efficient filter implementation.
• Detecting spikes based on criteria involving absolute and relative differences between raw and smoothed curves.
• Estimating peak maxima positions using second and third derivatives.

Main Results:

• The proposed Wiener filter method effectively detects spurious spikes in TLD glow curves.
• The method provides accurate dose evaluation by minimizing noise interference.
• Additional computational effort yields reliable estimates of peak maxima positions.
• The technique offers a valuable tool for glow curve quality control.

Conclusions:

• The Wiener filter approach offers a robust and efficient solution for spurious spike detection in TLD.
• This method enhances the reliability of dose assessment in thermoluminescence dosimetry.
• The integrated peak maxima estimation improves overall glow curve analysis and quality control.