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Updated: Nov 17, 2025
Visualization of Low-Level Gamma Radiation Sources Using a Low-Cost, High-Sensitivity, Omnidirectional Compton Camera
Published on: January 30, 2020
Neural network method for localization of radioactive sources within a partially coded field-of-view in
Qi Liu1, Yi Cheng1, Xianguo Tuo1
1College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, 610059, PR China; Sichuan University of Science and Engineering, Zigong, 643000, PR China.
Abstract:
Coded-aperture imagers typically have a smaller field-of-view (FOV) than in un-collimated gamma imaging systems. However, sources out of the fully coded field-of-view (FCFOV) can cause pseudo hotspots on the wrong side of an image reconstructed using the cross-correlation method. In this work, we propose a neural network method to identify and localize the sources within the partially coded field-of-view (PCFOV). The model was trained using Monte Carlo simulation data and evaluated with both simulation and experimental data. The results showed that the proposed model can identify and localize sources with good classification accuracy, low positioning error, and strong robustness to the statistical noise.
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