Regularizing RMC images for locating mid-range point sources

Abstract

A: A rotating modulation collimator (RMC) is a useful technique for sensing remote radiation sources. Recently, Kowash and his colleagues presented an image reconstruction algorithm to detect mid-range point sources with the RMC. However, their algorithm tends to produce undesirable artifacts in the reconstructed images. In this paper, we propose an improved image reconstruction algorithm using a regularization method. Our algorithm reduces the artifacts by increasing the sparsity during the reconstruction. We demonstrate the proposed algorithm on simulation data from RMC system model and MCNP data. K: Data processing methods; Image filtering; Inspection with gamma rays; Search for radioactive and fissile materials 1Corresponding author.

Dual-Particle Imaging Performance of a Cs2LiYCl6:Ce (CLYC)-Based Rotational Modulation Collimator (RMC) System

“…In order to convert modulation patterns into radiation images of the source distribution, we employed the MLEM method with the regularization process that can eliminate artifacts (noisy image pixels with relatively high maximum likelihood estimation (MLE) value occasionally appearing in the course of the MLEM iteration process) by assigning an adaptive weight to each pixel. It reduces the artifact by increasing the sparsity of estimation during the reconstruction [19,24]. It was confirmed experimentally that this approach could distinguish two sources and estimate source positions correctly when the relative ratio of intensity from the two 133 Ba sources was less than 3.53 [24].…”

“…RMC is an indirect imaging technique that uses temporal modulation patterns, we also studied the imaging reconstruction methodology to mapping acquired data on two-dimensional (2-D) radiation source distribution [14,19]. The reconstructed images can be obtained by the maximum likelihood expectation maximization (MLEM) approach.…”

A Monte Carlo simulation study for the gamma-ray/neutron dual-particle imager using rotational modulation collimator (RMC)

“…In this paper, we mainly focused on the optimization of design parameters for the dual-particle imaging purpose, and on the demonstration of the feasibility to develop a dual-particle imager. We proposed a laminated mask design consisting of 1 cm thick Pb and 0.2 cm thick BPE, and we also developed the image reconstruction algorithm utilizing MLEM, to estimate spatial distributions of gamma-ray and neutron sources, on the basis of previous research (Shin et al 2016a(Shin et al , 2016b. In the present study, we used a bilaterally symmetric mask design for RMC, and observed the existence of an intrinsic artifact in the reconstructed image because of the 180°periodicity in the modulation pattern.…”

Design and Fabrication of CLYC-Based Rotational Modulation Collimator (RMC) System for Gamma-Ray/Neutron Dual-Particle Imager

“…Maximum-likelihood expectation-maximization (MLEM) algorithm-based image reconstruction methods have been extensively studied and utilized in the field of radiation imaging because of their inherent excellence in low-count high-noise problems [7,[11][12][13][14][15][16][17]. We have been developing techniques which can further improve the efficiency and performance of the MLEM-based image reconstruction algorithm, by stabilizing inherent statistical noise contributions from the radiation counting [18][19][20]. Newly developed reconstruction algorithms require less iteration to converge whilst achieving even better imaging performance in terms of the signal-to-noise ratio and the structural similarity index.…”