2020/03/31 by Sridhar Tripathy, Jaydeep Datta, Nayana Majumdar +1 · 9 citations
Physics and Astronomy · #Artificial intelligence #Astrophysics #COSMIC cancer database #Computer science #Cosmic ray #Detector #Image resolution #Muon #Nuclear physics #Optics #Particle Detector Development and Performance #Particle physics theoretical and experimental studies #Pattern recognition (psychology) #Physics #Radiation Detection and Scintillator Technologies #physics.ins-det
paper · pdf · doi:10.1088/1748-0221/15/06/p06029
published in Journal of Instrumentation 15(06), P06029 (Institute of Physics) · Change in Caption ,References
arxiv created 2020/05/02 · openalex publication_date 2020/06/26 · arxiv updated 2020/08/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
This work reports numerical simulations and statistical tests carried out to study the performance of a prototype imaging setup to be developed for material discrimination using Muon Scattering Tomography (MST). The reconstructed images have been processed with a Pattern Recognition Method (PRM) to discriminate the low-Z and high-Z materials. The same method has been applied to examine the performance of the setup in recognizing the shape of the test objects. Design parameters of the setup, such as, area of the muon detectors, their physical placement, along with detector performance (spatial resolution, etc.) have been discussed. To evaluate the efficacy of the newly proposed PRM, the results have been compared to another technique based on cluster finding.