RESUMEN
Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.
RESUMEN
Neutron double scatter imaging exploits the kinematics of neutron elastic scattering to enable emission imaging of neutron sources. Due to the relatively low coincidence detection efficiency of fast neutrons in organic scintillator arrays, imaging efficiency for double scatter cameras can also be low. One method to realize significant gains in neutron coincidence detection efficiency is to develop neutron double scatter detectors which employ monolithic blocks of organic scintillator, instrumented with photosensor arrays on multiple faces to enable 3D position and multi-interaction time pickoff. Silicon photomultipliers (SiPMs) have several advantageous characteristics for this approach, including high photon detection efficiency (PDE), good single photon time resolution (SPTR), high gain that translates to single photon counting capabilities, and ability to be tiled into large arrays with high packing fraction and photosensitive area fill factor. However, they also have a tradeoff in high uncorrelated and correlated noise rates (dark counts from thermionic emissions and optical photon crosstalk generated during avalanche) which may complicate event positioning algorithms. We have evaluated the noise characteristics and SPTR of Hamamatsu S13360-6075 SiPMs with low noise, fast electronic readout for integration into a monolithic neutron scatter camera prototype. The sensors and electronic readout were implemented in a small-scale prototype detector in order to estimate expected noise performance for a monolithic neutron scatter camera and perform proof-of-concept measurements for scintillation photon counting and three-dimensional event positioning.
RESUMEN
The ability to map and estimate the activity of radiological source distributions in unknown three-dimensional environments has applications in the prevention and response to radiological accidents or threats as well as the enforcement and verification of international nuclear non-proliferation agreements. Such a capability requires well-characterized detector response functions, accurate time-dependent detector position and orientation data, a digitized representation of the surrounding 3D environment, and appropriate image reconstruction and uncertainty quantification methods. We have previously demonstrated 3D mapping of gamma-ray emitters with free-moving detector systems on a relative intensity scale using a technique called Scene Data Fusion (SDF). Here we characterize the detector response of a multi-element gamma-ray imaging system using experimentally benchmarked Monte Carlo simulations and perform 3D mapping on an absolute intensity scale. We present experimental reconstruction results from hand-carried and airborne measurements with point-like and distributed sources in known configurations, demonstrating quantitative SDF in complex 3D environments.
