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Determining the sequence of Compton scattering and photoelectric absorption events for a Compton camera system through timing information is difficult due to the finite timing resolution of radiation detectors. The conventional method compares the energies of two sequential events and determines the order of these events. The deep learning method can estimate the sequence of Compton scattering followed by the photoelectric effect better than the conventional method because it determines the sequence based on both energy and positional information of the radiation interaction. The initial information of the deep learning models is the position and energy information, and the input data are then processed in the nodes of the hidden layers. In this study, the performance of deep learning models for Compton sequence estimation and the effect of position information on these methods were investigated. The accuracies of the deep learning method and the conventional comparison method were compared. The weights connecting each node were analyzed to evaluate the effects of position and energy information to determine the Compton sequence.

Background: Cadmium zinc telluride (CZT) is a promising material because of a high detection efficiency, good energy resolution, and operability at room temperature. However, the cost of CZT dramatically increases as its size increases. In this study, to achieve a large effective volume with relatively low cost, an array structure comprised of individual virtual Frisch-grid CZT detectors was proposed. Materials and Methods:The prototype consisted of 2 × 2 CZTs, a holder, anode and cathode printed circuit boards (PCBs), and an application-specific integrated circuit (ASIC). CZTs were used and the non-contacting shielding electrode method was applied for virtual Frisch-grid effect. An ASIC was used, and the holder and the PCBs were fabricated. In the current system, because the CZTs formed a common cathode, a total of 5 channels were assigned for data processing. Results and Discussion:An experiment using 137 Cs at room temperature was conducted for 10 minutes. Energy and timing information was acquired and the depth of interaction was calculated by the timing difference between the signals of both electrodes. Based on obtained three-dimensional position information, the energy correction was carried out, and as a result the energy spectra showed the improvements. In addition, a Compton image was reconstructed using the iterative method. Conclusion:The virtual Frisch-grid CZT detector based on the array structure was developed and the energy spectra and the Compton image were successfully acquired.