Room: ePoster Forums
Purpose: Protoacoustic has been addressed with the method by obtaining the depth of Bragg-peak (BP) measuring the time-of-flight of the pressure wave. However, the method in the clinic has a drawback since multitudinous measured signals were averaged to identify the accurate signal peak from the indiscernible noises. The aim of this study is to investigate if advanced signal processing technique can significantly improve the signal-to-noise ratio (SNR) of protoacoustic signals, which would reduce the delivered dose and make protoacoustic signals useful for proton range verification.
Methods: All the acoustic signals were averaged by setting up the oscilloscope. The average 1024 was used as the reference to identify the accurate acoustic location. We used db3 wavelet transform to decompose the collected signals to extract and isolate the noise from the total signals and to recover the useful protoacoustic signals. The majority of the noise was reduced using the high-pass subbands in a multiresolution level. We manually selected both hard and soft thresholding in the wavelet domain for the averaged data (i.e., avg1, avg8, avg16, â€¦ avg1024, the sampling frequency is 15.625 MHz).
Results: We have performed the signal de-noising using wavelet transform and extracted the BP peak of each signal. The BP signal has been sharply defined up to the average 8 signals that can convert to the dose (<1.5 Gy). The distinguishable BP peak point for all the averaged signals was equally 2531.
Conclusion: We proposed a wavelet-based denoising method to significantly reduce noise in collected photoacoustic signals and improve the BP identification accuracy with a few signal averages and demonstrated it feasibility. This denoising technique will be very useful for future 2D/3D protoacoustic imaging an could reduce the delivered dose and make protoacoustic clinically useful for proton range verification.