Abstract
Parallax error decreases the accuracy of the Positron Emission Tomography (PET) scanner. One of suitable solutions to reduce this error is to gain the depth of interaction information in a PET which uses the phoswich detectors. The pulse shape of the scintillator material can identify the corresponding layer of interaction within the phoswich detector by using Pulse Shape Discrimination (PSD) methods. In this work, we propose the PSD based on a Discrete Fractional Fourier Transform (DFRFT) to extract the features of the scintillation pulses. Then, we use the Support Vector Machine (SVM) to classify these features. A data set consists of 100 000 scintillation pulses for LSO and LuYAP crystals are discriminated using the proposed method. Different fraction factors of the DFRFT are studied to select the optimum one. Also, the SVM is applied using linear, radial basis function, or quadratic kernel. The highest efficiency of the proposed PSD is 96.3% when the applied fraction factor is 0.8 and a quadratic SVM kernel is used.