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A homography method to correct position errors generated in the Compton imaging system using a resistive network is presented. The Compton imaging system is composed of a scatterer and an absorber in multichannel arrays for high resolution and can detect gamma rays emitted from radioisotopes. Resistive networks are often used in this system to efficiently reduce the number of channels. However, this can cause position errors, and the spatial resolution deteriorates according to the resistance value of the network, type of detector array, and characteristics of the preamplifier used. Therefore, before tracking the position of the source, it is necessary to correct the position errors of images obtained from the scatterer and absorber. Also, a new correction method should consider the characteristics of the readout circuits based on the resistive network. In this work, the position errors are corrected using homography, which is a coordinate transformation method. To verify the corrections using homography transformation, we modeled the current pulse generated from the detector and designed an automatic channel selection circuit to input each channel of the resistive network. From experiments, we first obtained the positions with distortions according to the setup of readout circuits and corrected these errors by applying the homography transformation method. Consequently, the distortions were significantly corrected, and the error rates of the positions compared with those of the ideal grid were greatly reduced by up to 0.36%. [ABSTRACT FROM AUTHOR]

Accurate screening of sewer conditions from monitoring data contributes to maintaining their operations (in terms of water quality and quantity) safe as well as reducing their associated costs (for operation and maintenance). This study was designed to assess the performance deterioration in sewer systems using a series of data classification tools, namely classical classification and novel supervised learning algorithms. The hydraulic data available for four sewer systems at Jinju City in Korea in a daily format during the monitoring period of 2013–2017 were provided as example data sets to those algorithms, which were evaluated independently with 70% training and 30% test data sets randomly divided. A self-organizing map (SOM) with a specialty in extracting hidden patterns in data was used to classify the data sets into three warning levels in the absence of any definite warning criteria for individual parameters. Our findings showed that three supervised learning algorithms achieved comparable performance in predicting warning levels defined from SOM to exiting classification algorithm in terms of accuracy and error rate. The network architecture optimized for supervised learning algorithms, in fact, varied significantly depending on the data sets, including that with additional variables on top of the original data set. In contrast, exiting classification algorithm unexpectedly produced high error rates in case that the hydraulic parameters had low coefficient of variation values reaching as high as 16%. Overall, these results demonstrated that novel supervised learning algorithms were more universally applicable for the assessment of hydraulic and/or water quality conditions in sewer systems than classical classification algorithm, regardless of the amount of variability in the data sets. [ABSTRACT FROM AUTHOR]

The Compton camera can provide 3-D images of radioactive material distribution based on a single measurement at a fixed position. The Compton camera also can image several different kinds of radioactive materials simultaneously, by means of the "multitracing" capability. In the present study, this multitracing capability was tested for a double-scattering-type Compton camera, or Double-Scattering Compton Imager (DOCI), which utilizes two double-sided silicon strip detectors (DSSDs) and one NaI(Tl) scintillation detector. Our experimental result shows that the 137Cs and 60Co gamma sources can be clearly distinguished in 2-D and 3-D Compton images, and that there is no significant interference between the two gamma sources. The imaging resolutions were determined to be 6.2 and 4.7 mm FWHM for the 137Cs (662 keV) and 60Co (1332 keV) point sources at 4 cm, respectively. The angular resolutions, determined from the angular resolution measure (ARM) distributions, were 7.3 and 6.5° for the source energies of 662 and 1332 keV, respectively. The DOCI remains under development; its imaging resolution will be further improved with the incorporation of more sophisticated detectors and the related electronics, including a faster scintillation detector (LYSO) and higher-spatial-resolution position-sensitive detectors. [ABSTRACT FROM AUTHOR]

A digital pulse-shape method (DPSM) is proposed to improve the time resolution of a BaF2 scintillation detector for low-energy gamma rays. By using chi-square fitting of digitally measured pulse shapes with calculated shapes, the proposed DPSM determined the pulse height and the start time corresponding to the deposited energy and the interaction moment, respectively, of gamma rays incident on the BaF2 scintillator. We calculated theoretical pulse shapes by considering light output, light-attenuation length, and light path within the scintillator. In particular, we calculated the light path inside the scintillator by using a Monte Carlo method. We performed coincidence measurements for gamma rays emitted from 22Na and 133Ba standard sources with two cylindrical BaF2 scintillation detectors and then we obtained a time resolution of around 6 ns for 81-keV and 511-keV gamma rays by using the DPSM. Although time resolution obtained using the DPSM was inferior to that obtained using a conventional analog signal process, it had a consistent value irrespective of gamma-ray energy. [ABSTRACT FROM AUTHOR]

In the present study, a Compton camera simulator based on the GEANT4 detector simulation tool kit and MATLAB™ and designated the Compton Imaging Simulator (CIS), was developed. The software system encompasses a simulator, an image-reconstruction algorithm, and a data analysis tool. The computational time to obtain a sufficient number of Compton scattered data was dramatically reduced using the source-biasing and exponential transform techniques. Also, a four-dimensional Monte Carlo simulation capability was incorporated. A comparison of the simulation results with the experimental results shows that the CIS accurately simulates the Compton camera. [ABSTRACT FROM AUTHOR]

A Compton camera is usually composed of a scatterer detector and an absorber detector. The interaction position resolution of the absorber detector is the critical or limiting detector parameter that most seriously affects the imaging resolution of the table-top Compton camera currently under development in our group. Currently, it is assumed that all interactions occur at the centers of the detector segments of the absorber detector (25-segmented germanium detector), which is a simple but obviously not the best practice, considering that the interaction depths of the photons in the absorber detector, especially of low-energy photons, are not distributed uniformly. More photons have interaction in the front region of the detector due to the limited penetrating depth of the photons. Therefore, the present study developed a novel, "average interaction depth (AID)" method, which improves the imaging resolution of Compton camera by additionally considering the average interaction depth of the incident photon in the absorber detector. Simulations with Geant4 showed that the imaging resolution of the Compton camera can be significantly improved by using the AID method. For example, the resolution for a 511 keV γ point source was improved from 9.9 mm to 7.6 mm in full width at half maximum (FWHM). For a 364 keV γ point source, the improvement was even more significant from 11.4 mm to 7.2 mm. [ABSTRACT FROM AUTHOR]