Experimental evaluation of reconstruction algorithms for scintillation crystal array based on charge projection readout

Although the technological advances in hardware of gamma camera lead to an obvious increase of detector performance, the final reconstructed image is still strongly restricted by reconstruction algorithms. In this work, an experiment evaluation of four popular algorithms, i.e., truncated Center-of-Gravity (TCOG), Raise-to-Power (RTP), Least Squares Estimator based on Particle Swarm Optimization (PSO-LSE) and Gaussian fitting (GF), for estimating the position of scintillation events detected by scintillation crystal array based on charge projection readout is performed. The detector of the gamma camera consists of a 22×22 array of CsI(Tl) scintillation crystals and an 8×8 matrix of SiPM pixels. The readout circuit, known as symmetric charge division (SCD) circuit, reduces an 8×8 array of signal channels into 8+8 signal channels coming from rows and columns projections. The imaging performances, in terms of flood image, average peak-to-valley ratio of line profile, useful field-of-view (UFOV) and position linearity response are measured. The result indicates that the four presented algorithms show good applicability for charge projection readout. RTP and PSO-LSE algorithms perform better in pixel identification of flood image and peak-to-valley of line profile, and PSO-LSE and GF methods are helpful to increase the UFOV. Among the four implemented reconstruction algorithms, PSO-LSE is a potential and promising algorithm that allows achieving excellent pixel identification of flood image, peak-to-valley ratio of line profile, spatial resolution, UFOV and position linearity response at the same time. The application of the PSO-LSE algorithm may offer the possibility to obtain high-quality reconstructed image in scintillation crystal array based on charge projection readout.