<p>In our previous work on image reconstruction for single-layer collimatorless scintigraphy, we introduced the min-min weighted robust least squares (WRLS) optimization algorithm to address the challenge of reconstructing images when both the system matrix and the projection data are uncertain. Whereas the WRLS algorithm has been successful in two-dimensional (2D) reconstruction, expanding it to three-dimensional (3D) reconstruction is difficult since the WRLS optimization problem is neither smooth nor strongly-convex. To overcome these difficulties and achieve robust image reconstruction in the presence of system uncertainties and projection noise, we propose a generalized iterative method based on the maximum likelihood expectation maximization (MLEM) algorithm, hereinafter referred to as the Masked-MLEM algorithm. In the Masked-MLEM algorithm, only selected subsets (``masks'') in the system matrix and the projection contribute to the image update to satisfy the constraints imposed by the system uncertainties. We validate the Masked-MLEM algorithm and compare it to the standard MLEM algorithm using data from both collimated and uncollimated imaging instruments, including parallel-hole collimated SPECT, 2D collimatorless scintigraphy, and 3D collimatorless tomography. The results show that the Masked-MLEM and standard MLEM reconstructions are similar in SPECT imaging, while the Masked-MLEM algorithm outperforms the standard MLEM algorithm in collimatorless imaging. A good choice of system uncertainty can make the Masked-MLEM reconstruction more robust than the standard MLEM reconstruction, effectively reducing the likelihood of reconstructing higher activities in regions without radioactive sources.</p>

<p>In our previous work on image reconstruction for single-layer collimatorless scintigraphy, the min-min weighted robust least squares (WRLS) optimization algorithm was proposed to address a general reconstruction problem in which both the system matrix and the projection data are uncertain. Whereas the WRLS algorithm has been successful in two-dimensional (2D) reconstruction, expanding this algorithm to three-dimensional (3D) reconstruction is difficult. To solve the WRLS optimization problem for more robust image reconstruction, we propose a generalized iterative method based on the maximum likelihood expectation maximization (MLEM) algorithm, hereinafter referred to as the Masked-MLEM algorithm. In the Masked-MLEM algorithm, only selected subsets (``masks'') in the system matrix and the projection will contribute to the image update in order to satisfy the constraints on the system uncertainties. We validate the Masked-MLEM algorithm and compare it to the standard MLEM algorithm using data from both collimated and uncollimated imaging instruments, including parallel-hole collimated SPECT, 2D collimatorless scintigraphy, and 3D collimatorless tomography. The results show that in SPECT imaging the Masked-MLEM and standard MLEM reconstructions are similar, and in collimatorless imaging, the Masked-MLEM algorithm outperforms the standard MLEM algorithm. A good choice of system uncertainty can make the Masked-MLEM reconstruction more robust than the standard MLEM reconstruction in both collimated and uncollimated imaging. Furthermore, the computation time of each Masked-MLEM iteration is comparable to that in the standard MLEM algorithm. Although, the memory consumption of the Masked-MLEM algorithm is higher due to the storage of the system matrix uncertainties.</p>

<p>In our previous work on image reconstruction for single-layer collimatorless scintigraphy, the min-min weighted robust least squares (WRLS) optimization algorithm was proposed to address a general reconstruction problem in which both the system matrix and the projection data are uncertain. Whereas the WRLS algorithm has been successful in two-dimensional (2D) reconstruction, expanding this algorithm to three-dimensional (3D) reconstruction is difficult. To solve the WRLS optimization problem for more robust image reconstruction, we propose a generalized iterative method based on the maximum likelihood expectation maximization (MLEM) algorithm, hereinafter referred to as the Masked-MLEM algorithm. In the Masked-MLEM algorithm, only selected subsets (``masks'') in the system matrix and the projection will contribute to the image update in order to satisfy the constraints on the system uncertainties. We validate the Masked-MLEM algorithm and compare it to the standard MLEM algorithm using data from both collimated and uncollimated imaging instruments, including parallel-hole collimated SPECT, 2D collimatorless scintigraphy, and 3D collimatorless tomography. The results show that in SPECT imaging the Masked-MLEM and standard MLEM reconstructions are similar, and in collimatorless imaging, the Masked-MLEM algorithm outperforms the standard MLEM algorithm. A good choice of system uncertainty can make the Masked-MLEM reconstruction more robust than the standard MLEM reconstruction in both collimated and uncollimated imaging. Furthermore, the computation time of each Masked-MLEM iteration is comparable to that in the standard MLEM algorithm. Although, the memory consumption of the Masked-MLEM algorithm is higher due to the storage of the system matrix uncertainties.</p>

As part of the Light Water Reactor and Sustainability (LWRS) program in the U.S. Department of Energy (DOE) Office of Nuclear Energy, material aging and degradation research is currently geared to support the long-term operation of existing nuclear power plants (NPPs) as they move beyond their initial 40 year licenses. The goal of this research is to provide information so that NPPs can develop aging management programs (AMPs) to address replacement and monitoring needs as they look to operate for 20 years, and in some cases 40 years, beyond their initial, licensed operating lifetimes. For cable insulation and jacket materials that support instrument, control, and safety systems, accelerated aging data are needed to determine priorities in cable aging management programs. Before accelerated thermal and radiation aging of harvested, representative cable insulation and jacket materials, the benchmark performance of a new test capability at Oak Ridge National Laboratory (ORNL) was evaluated for temperatures between 70 and 135°C, dose rates between 100 and 500 Gy/h, and accumulated doses up to 200 kGy. Samples that were characterized and are representative of current materials in use were harvested from the Callaway NPP near Fulton, Missouri, and the San Onofre NPP north of San Diego, California. From the Callaway NPP, a multiconductor control rod cable manufactured by Boston Insulated Wire (BIW), with a Hypalon/ chlorosulfonated polyethylene (CSPE) jacket and ethylene-propylene rubber (EPR) insulation, was harvested from the auxiliary space during a planned outage in 2013. This cable was placed into service when the plant was started in 1984. From the San Onofre NPP, a Rockbestos Firewall III (FRIII) cable with a Hypalon/ CSPE jacket with cross-linked polyethylene (XLPE) insulation was harvested from an on-site, climate-controlled storage area. This conductor, which was never placed into service, was procured around 2007 in anticipation of future operation that did not occur. Benchmark aging for both jacket and insulation material was carried out in air at a temperature of 125°C or in a uniform 140 Gy/h gamma field over a period of 60 days. Their mechanical properties over the course of their exposures were compared with reference data from comparable cable jacket/insulation compositions and aging conditions. For both accelerated thermal and radiation aging, it was observed that the mechanical properties for the Callaway BIW control rod cable were consistent with those previously measured. However, for the San Onofre Rockbestos FRIII, there was an observable functional difference for accelerated thermal aging at 125°C. Details on possible sources for this difference and plans for resolving each source are given in this paper.