Deep Learning-Based Pulse Height Estimation for Separation of Pile-Up Pulses From NaI(Tl) Detector

Measured spectra in a high count rate environment are difficult to analyze because of the spectral distortions caused by the pulse pile-up effect. This study proposes a deep learning-based method for separating and predicting the true pulse height of a signal with pulse pile-up events for application to radiation measurement and spectroscopy with a scintillation detector. To train the deep learning model, pulse signals simulating scintillation pulses were prepared by using a predefined mathematical model with parameters determined by analysis of the scintillation pulse measured from a NaI(Tl) detector. To simulate realistic scintillation pulses, Gaussian noises corresponding to thermal and shot noises were added to the signals. The trained model was validated with signals measured from two gamma-ray sources, Na-22 and Cs-137. The model was then evaluated using two performance indicators, restoration and separation rates, which represent how much the net count is restored in the region of interest (ROI) and the separation accuracy depending on the time interval. As a result, the deep learning model was confirmed to correctly estimate the pulse heights in a high pile-up environment up to certain restoration and separation rates.N

Development and Characterization of Tissue Equivalent Proportional Counter for Radiation Monitoring in International Space Station

Tissue equivalent proportional counter (TEPC) can measure the Linear Energy Transfer (LET) spectrum and calculate the equivalent dose for the complicated radiation field in space. In this paper, we developed and characterized a TEPC for radiation monitoring in International Space Station (ISS). The prototype TEPC which can simulate a 2 μm of the site diameter for micro-dosimetry has been tested with a standard alpha source (241Am, 5.5 MeV). Also, the calibration of the TEPC was performed by the 252Cf neutron standard source in Korea Research Institute of Standards and Science (KRISS). The determined calibration factor was kf = 3.59×10-7 mSv/R