Pulse pile-up correction by auto-regression on linear operations (ARLO) method: A comparison with integration-based algorithms
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Radiation detection at high count rate suffers from pulse pile-up, where the counting data and energy information of the system are affected by the overlapping of the system output pulses. There exist various pile-up correction strategies to recover the true information of the pulses, among which pulse-tail extrapolation is a well-known method focused on in this study. Present work aims to use a mono-exponential model for extrapolating the pileup-distorted trailing edge of a pulse, to provide a reference line for calculating the true amplitude of its subsequent overlapping pulse. To this goal, the auto-regression on linear operations (ARLO) method is examined and compared with two integrationbased methods (the Foss and the Matheson methods), as well as the non-linear least squares (NLS) method. Despite a higher sensitivity to noise, the ARLO method was able to provide a simple, non-iterative solution with a performance over 400 times faster than the NLS algorithm, according to the analysis of a high count rate set of experimental pulses from a NaI(Tl) detection system. Foss and Matheson methods also provided solutions reasonably faster than NLS (but not surpassing ARLO), performing exactly the same as each other with results very close to NLS, benefiting from their non-iterative nature.
Abstract
Radiation detection at high count rate suffers from pulse pile-up, where the counting data and energy information of the system are affected by the overlapping of the system output pulses. There exist various pile-up correction strategies to recover the true information of the pulses, among which pulse-tail extrapolation is a well-known method focused on in this study. Present work aims to use a mono-exponential model for extrapolating the pileup-distorted trailing edge of a pulse, to provide a reference line for calculating the true amplitude of its subsequent overlapping pulse. To this goal, the auto-regression on linear operations (ARLO) method is examined and compared with two integrationbased methods (the Foss and the Matheson methods), as well as the non-linear least squares (NLS) method. Despite a higher sensitivity to noise, the ARLO method was able to provide a simple, non-iterative solution with a performance over 400 times faster than the NLS algorithm, according to the analysis of a high count rate set of experimental pulses from a NaI(Tl) detection system. Foss and Matheson methods also provided solutions reasonably faster than NLS (but not surpassing ARLO), performing exactly the same as each other with results very close to NLS, benefiting from their non-iterative nature.
참고문헌 (25)
- G. F. Knoll, "Radiation Detection and Measurement" (2010), John Wiley & Sons
- N. Tsoulfanidis, "Measurement and Detection of Radiation" (2015), CRC Press
- S. Usman, "Radiation detector deadtime and pile up : a review of the status of science", Nucl. Eng. Technol, 50(7)), pp.1006~1016 (2018)
- M. Yousaf, "A comparison of traditional and hybrid radiation detector dead-time models and detector behavior", Prog. Nucl. Energy, 83, pp.177~185 (2015)
- M. -R. Mohammadian-Behbahani, "Two-channel combination methods for count-loss correction in radiation measurements at high rates and with pulsed sources", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, pp.167195~ (2022)
- S. H. Lee, "A new G–M counter dead time model", Appl. Radiat. Isot, 53(4–5), pp.731~737 (2000)
- B. Almutairi, "Voltage dependent pulse shape analysis of Geiger-Müller counter", Nucl. Eng. Technol, 51(4), pp.1081~1090 (2019)
- M. Hoheisel, "Review of medical imaging with emphasis on X-ray detectors", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, 563(1), pp.215~224 (2006)
- R. Ballabriga, "Photon counting detectors for X-ray imaging with emphasis on CT", IEEE Trans. Radiat. Plasma Med. Sci, 5(4), pp.422~440 (2020)
- A. Vignati, "Innovative solid state detectors for A new beam monitoring in proton therapy", 2019 AAPM (American Association of Physics in Medicine) annual meeting, 46(6), pp.425~426 (2019)
- N. Cartiglia, "LGAD designs for future particle trackers", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, 979, pp.164383~ (2020)
- M. -R. Mohammadian-Behbahani, "A comparison study of the pile-up correction algorithms", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, 951, pp.163013~ (2020)
- M. Nakhostin, "Signal Processing for Radiation Detectors" (2017), John Wiley & Sons
- M. Lee, "Pulse pileup correction method for gamma-ray spectroscopy in high radiation fields", Nucl. Eng. Technol, 52(5), pp.1029~1035 (2020)
- M. -R. Mohammadian-Behbahani, "Non-iterative pulse tail extrapolation algorithms for correcting nuclear pulse pile-up Nucl", Eng. Technol, 55(12), pp.4350~4356 (2023)
- M. R. Mohammadian-Behbahani, "A pulse pile-up correction method for high-rate radiation spectroscopy", 1st International & 28th National Conference on Nuclear Science and Technology (ICNST22) (2022)
- H. B. Yang, "A digital pulse fitting method for the alpha decay studies of shortlived nuclei", Eur. Phys. J. A, 55(1), pp.8~ (2019)
- M. -R. Mohammadian-Behbahani, "Integral-equation based methods for parameter estimation in output pulses of radiation detectors: application in nuclear medicine and spectroscopy", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, 887, pp.7~12 (2018)
- F. Belli, "A method for digital processing of pile-up events in organic scintillators", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, 595(2), pp.512~519 (2008)
- H. Yang, "Efficient pile-up correction based on pulse-tail prediction for high count rates", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, 1029, pp.166376~ (2022)
- M. -R. Mohammadian-Behbahani, "Pile-up correction algorithm based on successive integration for high count rate medical imaging and radiation spectroscopy", Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip, 897, pp.1~7 (2018)
- M. Pei, "Algorithm for fast monoexponential fitting based on auto-regression on linear operations(ARLO)of data", Magn. Reson. Med, 73(2), pp.843~850 (2015)
- S.D. Foss, "A method of exponential curve fitting by numerical integration", Biometrics, pp.815~821 (1970)
- I. B. C. Matheson, "The method of successive integration : a general technique for recasting kinetic equations in a readily soluble form which is linear in the coefficients and sufficiently rapid for real time instrumental use", Instrum. Sci. Technol, 16, pp.345~373 (1987)
- K. Tittelbach-Helmrich, "An integration method for the analysis of multiexponential transient signals", Meas. Sci. Technol, 4(12), pp.1323~ (1993)