Gamma Emission Tomography Research Articles

Image reconstruction method of gamma emission tomography based on prior-aware information and machine learning for partial-defect detection of PWR-type spent nuclear fuel

Spent nuclear fuel (SNF) requires accurate and effective supervision to prevent radiation release to the public and the environment. Gamma emission tomography (GET) has been used to inspect partial-defects at the pin-by-pin level through the acquisition of tomographic images. However, due to the high density of nuclear fuel rods, GET shows relatively low accuracy for the central region. This study proposes an image reconstruction method for the internal fuels based on Monte Carlo simulation and machine learning algorithm. The gammas from the SNF were measured with the GET device and the sinograms were reconstructed with Maximum-Likelihood Expectation-Maximization (MLEM) with prior-aware information of SNF, and image quality was improved with the machine learning technique. Our results show that the MLEM with prior-aware information could dramatically improve the image quality and the denoising technique with the machine learning could clearly correct the over-and under-estimation. Based on the results of quantitative validation of the proposed reconstruction method, the pattern classification accuracy was calculated to be about 100 %. These techniques enabled the image acquisition of the central fuel rod and increased accuracy in partial defect detection. For further study, the performance of the proposed reconstruction method will be evaluated based on the experiment data.

Performance evaluation of Yonsei Single-photon Emission Computed Tomography (YSECT) for partial-defect inspection within PWR-type spent nuclear fuel

As the amount of power generated by nuclear power plants increases, the importance of managing Spent Nuclear Fuel (SNF) to prevent proliferation increases as well. In a previous study, we optimally designed the gamma emission tomography instrument named Yonsei Single-photon Emission Computed Tomography version 2 (YSECT.v.2) based on Monte Carlo (MC) simulation for inspection and detection of defects in SNF. The objective of the current study was to fabricate a prototype YSECT.v.2 instrument and to evaluate its performance. The YSECT.v.2 instrument consists of scintillator-based detection modules, a multi-channel data acquisition (DAQ) module, a heat reduction module, and a waterproof housing. Based on the experimental results for a mock-up of fresh nuclear fuel rods, the spatial resolution of the prototype YSECT.v.2 instrument was determined to be 10.8 mm. In the experiment with 137Cs test sources, a high-quality image could be obtained with the exclusion of the pixel value below the threshold. For a 6 × 6 array, the spatial resolution for 137Cs was analyzed to be 7.2 mm. Considering these results, we expected that source distribution could be distinguishable using the YSECT.v.2. In the future, further experimentation will validate the performance of the fabricated instrument for a mock-up of SNF rods in water.

Optimization of Yonsei Single-Photon Emission Computed Tomography (YSECT) Detector for Fast Inspection of Spent Nuclear Fuel in Water Storage

Background: The gamma emission tomography (GET) device has been reported a reliable technique to inspect partial defects within spent nuclear fuel (SNF) of pin-by-pin level. However, the existing GET devices have low accuracy owing to the high attenuation and scatter probability for SNF inspection condition. The purpose of this study is to design and optimize a Yonsei single-photon emission computed tomography version 2 (YSECT.v.2) for fast inspection of SNF in water storage by acquisition of high-quality tomographic images.Materials and Methods: Using Geant4 (Geant4 Collaboration) and DETECT-2000 (Glenn F. Knoll et al.) Monte Carlo simulation, the geometrical structure of the proposed device was determined and its performance was evaluated for the 137Cs source in water. In a Geant4-based assessment, proposed device was compared with the International Atomic Energy Agency (IAEA)-authenticated device for the quality of tomographic images obtained for 12 fuel sources in a 14 × 14 Westinghouse-type fuel assembly.Results and Discussion: According to the results, the length, slit width, and septal width of the collimator were determined to be 65, 2.1, and 1.5 mm, respectively, and the material and length of the trapezoidal-shaped scintillator were determined to be gadolinium aluminum gallium garnet and 45 mm, respectively. Based on the results of performance comparison between the YSECT.v.2 and IAEA’s device, the proposed device showed 200 times higher performance in gamma-detection sensitivity and similar source discrimination probability.Conclusion: In this study, we optimally designed the GET device for improving the SNF inspection accuracy and evaluated its performance. Our results show that the YSECT.v.2 device could be employed for SNF inspection.

Feasibility study of spent fuel internal tomography (SFIT) for partial defect detection within PWR spent nuclear fuel

The International Atomic Energy Agency (IAEA) mandates safeguards to ensure non-proliferation of nuclear materials. Among inspection techniques used to detect partial defects within spent nuclear fuel (SNF), gamma emission tomography (GET) has been reported to be reliable for detection of partial defects on a pin-by-pin level. Conventional GET, however, is limited by low detection efficiency due to the high density of nuclear fuel rods and self-absorption. This paper proposes a new type of GET named Spent Fuel Internal Tomography (SFIT), which can acquire sinograms at the guide tube. The proposed device consists of the housing, shielding, C-shaped collimator, reflector, and gadolinium aluminum gallium garnet (GAGG) scintillator. For accurate attenuation correction, the source-distinguishable range of the SFIT device was determined using MC simulation to the region away from the proposed device to the second layer. For enhanced inspection accuracy, a proposed specific source-discrimination algorithm was applied. With this, the SFIT device successfully distinguished all source locations. The comparison of images of the existing and proposed inspection methods showed that the proposed method, having successfully distinguished all sources, afforded a 150 % inspection accuracy improvement.

In-air and in-water performance comparison of Passive Gamma Emission Tomography with activated Co-60 rods

A first-of-a-kind geological repository for spent nuclear fuel is being built in Finland and will soon start operations. To make sure all nuclear material stays in peaceful use, the fuel is measured with two complementary non-destructive methods to verify the integrity and the fissile content of the fuel prior to disposal. For pin-wise identification of active fuel material, a Passive Gamma Emission Tomography (PGET) device is used. Gamma radiation emitted by the fuel is assayed from 360 angles around the assembly with highly collimated CdZnTe detectors, and a 2D cross-sectional image is reconstructed from the data. At the encapsulation plant in Finland, there will be the possibility to measure in air. Since the performance of the method has only been studied in water, measurements with mock-up fuel were conducted at the Atominstitut in Vienna, Austria. Four different arrangements of activated Co-60 rods, steel rods and empty positions were investigated both in air and in water to confirm the functionality of the method. The measurement medium was not observed to affect the ability of the method to distinguish modified rod positions from filled rod positions. More extended conclusions about the method performance with real spent nuclear fuel cannot be drawn from the mock-up studies, since the gamma energies, activities, material attenuations and assembly dimensions are different, but full-scale measurements with spent nuclear fuel are planned for 2023.

Multi-parameter optimization of gamma emission tomography instruments for irradiated nuclear fuel examination

Material test reactors have an extended use in irradiation testing of novel nuclear fuel materials and the fuel behavior in off-normal conditions. The performance of the nuclear fuel is examined in in-pile and out-of-pile post-irradiation examinations (PIEs), e.g., using Gamma Emission Tomography (GET). GET is a nondestructive assay that images the internal spatial distribution of gamma-emitting nuclides built up in the fuel due to irradiation. Since GET can be performed close to the reactor and without intrusion in the fuel object, it can potentially speed up the data generation from PIE in irradiation testing.The performance metrics of GET devices can be identified regarding time requirements, noise in the reconstructed image, signal-to-background ratio, and spatial resolution. However, these are complicated to determine, partly due to inherent trade-offs between the metrics themselves, partly because they depend on the fuel activity and its spectrum (i.e., object dependent), and, finally, on the GET setup and its configuration.This work proposes a structured methodology for optimizing the collimator design for a new generation of GET tomography setups, intending to improve spatial resolution by one order of magnitude: from the millimeter scale to the hundred-micron scale. The conflicting performance metrics are determined based on the controllable parameters of the GET setup and the uncontrollable parameters of an anticipated fuel object, able to provide a signal-to-background ratio above a customized limit, chosen based on the specific application. The trade-off between the performance remaining metrics is then visualized by a Pareto approach, where dominated solutions are rejected. Finally, constraints on noise level and measurement time are used to find the optimal spatial resolution, without applying noise suppression filters.Two GET setups are presented using the outlined method. Firstly, to upgrade the tomography test bench BETTAN at Uppsala University, a new segmented HPGe detector is planned to be used with low-activity fuel rod mock-ups. Secondly, a GET system for investigating high-activity nuclear fuel rods of representative burnup. For a nuclear fuel inspection, the results showed that a spatial resolution of about 300 μm is possible with reasonable noise and measurement time constraints.

Vanquishing the computational cost of passive gamma emission tomography simulations leveraging physics-aware reduced order modeling

Passive Gamma Emission Tomography (PGET) has been developed by the International Atomic Energy Agency to directly image the spatial distribution of individual fuel pins in a spent nuclear fuel assembly and determine potential diversion. The analysis and interpretation of PGET measurements rely on the availability of comprehensive datasets. Experimental data are expensive and limited, so Monte Carlo simulations are used to augment them. However, Monte Carlo simulations have a high computational cost to simulate the 360 angular views of the tomography. Similar challenges pervade numerical science. With the aim to create a large dataset of PGET simulated scenarios, we addressed the computational cost of Monte Carlo simulations by developing a physics-aware reduced order modeling approach. This approach combines a small subset of the 360 angular views (limited views approach) with a computationally inexpensive proxy solution (real-time forward model) that brings the essence of the physics to obtain a real-time high-fidelity solution at all angular views but at a fraction of the computational cost. The method’s ability to reconstruct 360 views with accuracy from a limited set of angular views is demonstrated by testing its performance for different types of reactor fuel assemblies.

First Experimental Demonstration of the Use of a Novel Planar Segmented HPGe Detector for Gamma Emission Tomography of Mockup Fuel Rods

Postirradiation examination of nuclear fuel is routinely performed to characterize the important properties of current and future fuel. Gamma emission tomography is a proven noninvasive technique for this purpose. Among various measurement elements of the technique, a gamma-ray detector is an important element whose spectroscopic abilities and detection efficiency affect the overall results. Finding a combination of high detection efficiency and excellent energy resolution in a single detector is often a challenge. We have designed a novel planar segmented high-purity germanium detector that offers simultaneous measurement in six lines of sight with excellent energy resolution. The simultaneous detection ability enables faster data acquisition in a tomographic measurement, which may facilitate achieving higher spatial resolution. In this work, we have demonstrated the first use of the detector by performing a full tomographic measurement of mockup fuel rods. Two methods of detector data analysis were used to make spectra, and the images (tomograms) were reconstructed using the filtered back projection algorithm. The reconstructed images validate the successful use of the detector for tomographic measurement. The use of the detector for real fuel measurement is being planned and will be performed in the near future.

Experimental evaluation of the performance of a novel planar segmented HPGe detector for use in gamma emission tomography

The use of segmented HPGe detectors for gamma-ray tracking applications is well established. The spectroscopic capabilities of these detectors make them most suitable for such applications. For similar reasons, the use of such detectors in the tomographic measurement of irradiated nuclear fuel has also been envisioned. Especially, these detectors can facilitate faster fuel examination with excellent energy resolution. We have proposed and designed a novel planar segmented HPGe detector for use in gamma emission tomography. The design of the detector segmentation and the mode of operation is unique and offers six simultaneous detection channels for tomographic measurements. This work reports the first experimental evaluation of the performance of the detector. Important characteristics of the detector have been obtained, such as energy resolution of the segments in 1-fold (one segment) and 2-fold (two segments) modes, throughput curves, crosstalk energy corrections, and mislocalisation rate. Collimated source tests have been performed and the results have been compared with the MCNP simulations results. The obtained results are as expected and in good agreement with the simulation results, and it is estimated that using this detector can speed up the data collection by 3.2 times in comparison to an unsegmented detector of the same overall dimensions, in a tomographic application. Further improvements are foreseeable if scaling up to a larger detector with greater segmentation.

Performance Evaluation of an Imaging Radiation Portal Monitor System

An organic scintillator-based radiation portal monitor (RPM) prototype system with imaging capabilities has been developed based on the neutron–gamma emission tomography technique. The technique enables rapid detection and precise location of small amounts of special nuclear materials, such as plutonium, using time and energy correlations between fast neutrons and gamma rays from spontaneous fission with low false-alarm rates. These capabilities, in addition to state-of-the-art detection of various gamma-emitting sources, enables the novel imaging RPM concept to efficiently address global security threats from terrorism and the proliferation of nuclear weapons. The detector approach is simple and versatile and can easily be adapted for different applications in nuclear security, public safety, nuclear emergency response, and radiological surveying. In this work, basic performance parameters of the imaging RPM prototype system developed at KTH have been evaluated.

Improved Passive Gamma Emission Tomography image quality in the central region of spent nuclear fuel

Reliable non-destructive methods for verifying spent nuclear fuel are essential to draw credible nuclear safeguards conclusions from spent fuel. In Finland, spent fuel items are verified prior to the soon starting disposal in a geological repository with Passive Gamma Emission Tomography (PGET), a uniquely accurate method capable of rod-level detection of missing active material. The PGET device consists of two highly collimated detector banks, collecting gamma emission data from a 360° rotation around a fuel assembly. 2D cross-sectional activity and attenuation images are simultaneously computed. We present methods for improving reconstructed image quality in the central parts of the fuel. The results are based on data collected from 2017 to 2021 at the Finnish nuclear power plants with 10 fuel assembly types of varying characteristics, for example burnups from 5.7 to 55 GWd/tU and cooling times from 1.9 to 37 years. Data is acquired in different gamma energy windows, capturing the peaks of Cs-137 (at 662 keV) and Eu-154 (at 1274 keV), abundant isotopes in long-cooled spent nuclear fuel. Data from these gamma energy windows at well-chosen angles are used for higher-quality images, resulting in more accurate detection of empty rod positions. The method is shown to detect partial diversion of nuclear material also in the axial direction, demonstrated with a novel measurement series scanning over the edge of partial-length rods.

Calculation of Spatial Response of a Collimated Segmented HPGe Detector for Gamma Emission Tomography by MCNP Simulations

We have proposed a planar electronically segmented high-purity germanium (HPGe) detector concept in combination with a multislit collimator for gamma emission tomography. In this work, the spatial resolution achievable using the collimated segmented HPGe detector was evaluated, prior to the manufacture and operation of the detector. The spatial response of a collimated segmented HPGe detector concept was evaluated using simulations performed with Monte Carlo N-Particle (MCNP) transport code MCNP6. The full detector and multislit collimator system were modeled, and for the quantification of the spatial response, the modulation transfer function (MTF) was chosen as a performance metric. The MTF curve was obtained through the calculation of the line spread function (LSF) by analyzing the simulated projection data. In addition, tomographic reconstructions of the simulated simplified test objects were made to demonstrate the performance of the segmented HPGe detector in planned application. For 662-keV photons, the spatial resolution obtained was approximately the same as the collimator slit width for both the 100- and 150-mm-long collimators. The corresponding spatial resolution at 1596-keV photon energy was almost twice the slit width for the 100-mm collimator, due to the partial penetration of the high-energy gamma rays through the collimator bulk. For a 150-mm-long collimator, an improved resolution was obtained.

A Computational Methodology for Estimating the Detected Energy Spectra of the Gamma-Ray Flux From Irradiated Nuclear Fuel

Gamma-ray spectrometry using collimated detectors is a well-established examination method for irradiated nuclear fuel. However, the feasibility of examining a particular nuclide of interest is subject to constraints; the peak must be statistically determinable with the desired precision, and the total spectrum count rate in the detector should not cause throughput issues. Methods were assembled for gamma spectrum prediction to optimize instruments for gamma emission tomography and to enable <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> feasibility evaluation of determination of single peaks of irradiated nuclear fuel. The aim was to find reliable results (~10% accuracy) regarding total spectrum and peak count rates with faster computation time than a full-Monte Carlo approach. For this purpose, the method is based on depletion calculations with SERPENT2, a point-source kernel method for the collimator response, and a rig response matrix and a detector response matrix, both computed with MCNP6. The computational methodology uses the fuel properties (dimensions, materials, power history, and cooling time) and the instrumental setup (collimator and detector dimensions and materials) as an input. The prediction method was validated using the measured data from a high-burnup, short-cooled test fuel rodlet from the Halden reactor. Absolute count rates and ratios of characteristic peaks were compared between predicted and measured spectra, showing a total count rate overestimation of 7% and discrepancies between 2% and 20% for the single peaks (the same order of magnitude of the uncertainty). This level of agreement is deemed sufficient for measurement campaigns planning and the optimization of spectroscopic instruments for use in gamma scanning and tomography of nuclear fuel.

Bayesian Activity Estimation and Uncertainty Quantification of Spent Nuclear Fuel Using Passive Gamma Emission Tomography.

In this paper, we address the problem of activity estimation in passive gamma emission tomography (PGET) of spent nuclear fuel. Two different noise models are considered and compared, namely, the isotropic Gaussian and the Poisson noise models. The problem is formulated within a Bayesian framework as a linear inverse problem and prior distributions are assigned to the unknown model parameters. In particular, a Bernoulli-truncated Gaussian prior model is considered to promote sparse pin configurations. A Markov chain Monte Carlo (MCMC) method, based on a split and augmented Gibbs sampler, is then used to sample the posterior distribution of the unknown parameters. The proposed algorithm is first validated by simulations conducted using synthetic data, generated using the nominal models. We then consider more realistic data simulated using a bespoke simulator, whose forward model is non-linear and not available analytically. In that case, the linear models used are mis-specified and we analyse their robustness for activity estimation. The results demonstrate superior performance of the proposed approach in estimating the pin activities in different assembly patterns, in addition to being able to quantify their uncertainty measures, in comparison with existing methods.

Idea of an experimental technique for quantitative passive gamma emission tomography on irradiated nuclear fuel assemblies

An idea is presented in which passive gamma emission tomography of irradiated nuclear fuel is developed to enable quantitative information of the spatial activity distribution of selected isotopes within the fuel rods of the assembly. The idea is based on using well-known calibration sources mounted in the measurement device during measurement. The image reconstruction would include the sources, thereby enable quantification of the activity distribution. Should the idea be proven viable, the outcome would be valuable to the global community dealing with characterisation of nuclear fuel in terms of safety, security, safeguards and fuel development.

Evaluation of gamma-ray transmission through rectangular collimator slits for application in nuclear fuel spectrometry

Gamma-ray spectrometry is widely applied in several science fields, and in particular in non-destructive gamma scanning and gamma emission tomography of irradiated nuclear fuel. Often, a collimator is used in the experimental setup, to selectively interrogate a region of interest in the fuel. For the optimization of instrument design, as well as for planning measurement campaigns, predictive models for the transmitted gamma-ray intensity through the collimator are needed. Commonly, Monte Carlo radiation transport tools are used for accurate prediction of gamma-ray transport, however, the long computation time requirements when used in low-efficiency experimental setups present challenges.In this work, the full-energy peak intensity transmitted through a rectangular collimator slit was examined. A uniform planar surface source emitting isotropically was considered, and the rate of photons reaching an ideal counter plane on the opposite side of the collimator was evaluated by analytical integration. To find a closed-form primitive function, some idealizations were required, and thereby parametric models were obtained for the optical field of view, dependent on slit dimensions (length, height and width) and source-to-collimator distance. It was shown that the count rate in the detector is independent of the collimator-to-source distance. For contributions from outside the optical field of view, where a closed-form expression cannot be found, instead fast numerical integration methods were proposed.The results were validated using the Monte Carlo code MCNP6.2. For the analytical method, deviations were larger, the shorter the collimator, with up to 25% of underestimation obtained for the shortest examined collimator of 10 cm length. However, the longer the collimator, the better the observed agreement. This accuracy is deemed to be sufficient for instrument design and measurement planning, where often the order of magnitude of the count rate is not a priori known. For the numerical method, the results showed an agreement within 3% for all evaluated collimator settings.The methods are planned for use in iterative optimization routines in the design of Gamma Emission Tomography devices, as well as for the prediction of gamma spectra obtained in the planning of fuel inspections. An application of the proposed method was demonstrated in spectrum prediction for a short cooling-time fuel rod test from the Halden reactor.

Comparison of a semi-analytic variance reduction technique to classical Monte Carlo variance reduction techniques for high aspect ratio pencil beam collimators for emission tomography applications

A semi-analytic variance reduction technique developed for collimated gamma emission tomography problems was compared to classic Monte Carlo variance reduction techniques within the Monte Carlo N Particle Transport (MCNP) code. In the semi-analytic technique, a computationally efficient, non-analog, monodirectional source biased Monte Carlo simulation is first performed. Analytical expressions or empirical values are then used to correct for solid angle and field-of-view effects introduced by the non-analog source definition. This variance reduction technique was compared with deterministic transport sphere (DXTRAN) and geometry splitting variance reduction schemes to determine the accuracy and computational savings of each technique relative to an analog pulse height tally (F8 tally) at 1, 3, 5, and 10 mm collimator aperture radii. For radii 0.5 mm and 0.3 mm a DXTRAN sphere was used in place of an analog F8 tally, due to large particle history demands, to analyze the accuracy of the semi-analytic variance reduction technique. The computational savings and accuracy were evaluated for six to seven photopeaks depending on the method used. The monodirectional source biasing technique overestimated the count rates by approximately 9%–19% when the radius is less than 3 mm, but the technique overestimated by a factor of 2 to 7, when the radius is greater than or equal to 3 mm. The monodirectionally source biased technique offered computational saving factors on the order of 108-1013 over 1-10 mm collimator radii studied. DXTRAN and geometry splitting methods yielded higher accuracy, but computational savings range from approximately 0.13 to 2.2 and 0.07 to 2.9, respectively indicating marginal improvement at best.

Geometrical optimisation of a segmented HPGe detector for spectroscopic gamma emission tomography—A simulation study

Segmented coaxial HPGe (High Purity Germanium) detectors have recently been shown to be feasible for Gamma Emission Tomography (GET). This type of detector allows for a combination of high efficiency and high energy resolution in gamma spectrometry of irradiated nuclear fuel. The ultimate aim of developing segmented HPGe for GET measurements is to achieve a high spatial resolution to facilitate imaging of rod-internal features and interrogation of smaller irradiated fuel samples.In this work, we present the optimisation of a segmented HPGe detector through a simulation study using the Monte Carlo particle transport code MCNP. Constraints to each dimension of the detector were identified, from manufacturing limitations and requirements arising from the use of a finite-sized collimator slit. In particular, a relationship between the minimum inner radius of the coaxial detector and the segments azimuthal dimension was derived based on the identified constraints. Segment azimuthal and radial dimensions have been varied (based on the derived relationship between the azimuthal and radial dimension) and the full energy efficiency and misidentification rate were evaluated to obtain the optimal dimensions. The optimal ranges of the segment dimensions were determined.

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

Iterative reconstruction algorithm comparison using Poisson noise distributed sinogram data in passive gamma emission tomography

ABSTRACT Gamma emission tomography (GET) detects fuel rods that emit gamma rays for potential use as verification tools in nuclear safeguards. In GET, iterative reconstruction algorithms are often used to reconstruct passive gamma-ray emitter source distributions. Generally, using noisy sinogram data, the iterative reconstruction algorithms increase the noise level on a reconstruction image with iterations. Thus, it is important to evaluate how performances of representative iterative reconstruction algorithms change with noisy sinogram data. The passive gamma-ray source distributions inside the mock-up of the water-water energetic reactor (WWER) fuel assembly having missing fuel rods were reconstructed by using the following algorithms: gradient method, steepest descent method, conjugate gradient reconstruction method, algebraic reconstruction technique, simultaneous iterative reconstruction technique, and maximum likelihood expectation maximization (MLEM). Consequently, MLEM algorithm yielded a higher contrast reconstruction image and was regarded as higher reliable algorithm to discriminate the fuel rods from the passive gamma-ray emitter source distribution.