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This study investigates two unavoidable noise factors: electronic noise and radiation scattering, associated with detectors and their electronics. This study proposes a novel methodology to estimate electronic and scattering noise separately. It utilizes mathematical tools, namely, Kanpur theorem-1, standard deviation, similarity dice coefficient parameters, and experimental Computerized Tomography technique. Four types of gamma detectors: CsI (Tl), LaBr_3 (Ce), NaI (Tl) and HPGe are used with their respective electronics. A detector having integrated circuit electronics is shown to impart significantly less (~33% less) electronic noise in data as compared to detectors with distributed electronics. Kanpur Theorem-1 signature is proposed as a scattering error estimate. An empirical expression is developed showing that scattering noise depends strongly on mass attenuation coefficients of detector crystal material and weakly on their active area. The difference between predicted and estimated relative scattering is 14.6%. The methodology presented in this study will assist the related industry in selecting the appropriate detector of optimal diameter, thickness, material composition, and hardware as per requirement., Comment: 9 Figures and 15 Pages

Different technical and physical factors may affect the image quality reconstructed using a Computed Tomography system. We have developed and designed a 2D Gamma Computed Tomography set up to study the effect of some physical parameters. One must decide the number of detectors and set CT geometry parameters or configuration like the fan-beam angle and number of rotations. Usually, geometry parameters are determined based on the objects size. This study shows the influence of the density distribution of same-sized phantom or objects on CT geometry parameters. Due to limited space, industrial applications may not allow a CT system to move around the object (under investigation). On-spot customization of CT system configuration may be required according to similar situations. The same problem is experienced in medical science, material science, and many other fields in which the CT system is widely used for non-destructive imaging. The number of detectors in the scanning array is one major factor that optimizes a CT system. Of course, more detectors are desired for better resolution. Changing the number of detectors requires recalibration of CT geometry. A simulated work is presented to study the influence of the density distribution of same-sized objects and the number of detectors on CT system configuration. The same is verified experimentally also. A comparison between simulated and experimental results shows a good agreement., Comment: 4 PAGES, 6 figures, Zero Tables, submitted ICINDE 2022

Computed tomography (CT) has become a vital tool in a variety of fields as a result of technological developments and continual improvement. High-quality CT images are desirable for image interpretation and obtaining information from CT images. A variety of things influence the CT image quality. Various research groups have investigated and attempted to improve image quality by examining noise/error associated with CT geometry. This study aims to select detectors for CT, which yield the least amount of noise in projection data. Three distinct gamma-ray detectors that are routinely used in CT have been compared in terms of scattering and electrical noise. The sensitivity of Kanpur Theorem-1 to scattering noise is demonstrated in this work and used to quantify the relative level of scattering noise. The detector measures the signal multiple times, and the standard deviation of the signal is used to calculate the electronic noise. It is observed that IC CsI(Tl) scintillation detector produces low electronic noise and relative scattering noise as compared to conventional electronic detectors; NaI(Tl) and HPGe., Comment: 12 pages, 7 figures, Table 1, 37 references

Computed Tomography is one of the efficient and vital modalities of non-destructive techniques (NDT). Various factors influence the CT reconstruction result, including limited projection data, detector electronics optimization, background noise, detection noise, discretized nature of projection data, and many more. Radiation hardening and other aging factors that affect the operational settings may require recalibration of electronics parameters. Two well-known exercises are utilized with the motivation to improve reliability and accuracy in inverse recovery. The first exercise brute-forces an optimal candidate from the set of calibration methods for minimum error in inverse recovery. The second exercise, Kanpur Theorem-1 (KT-1) examines if optimal calibration sets electronics to impart minimum noise. The mutual conformity between statistics-derived CLT and Riemann integral transform-based KT-1 is shown first time using gamma radiation measurement. The analysis shows that measurement data with normal distribution inflicts the least noise in inverse recovery., Comment: 6 pages, 6 figures, 1 Table

Data set generated from the scintillation detector is used to build a mathematical model based on three different algorithms: (a) Multiple Polynomial Regression (b) Support Vector Regression (c) Neural Network algorithm. Using visualizations and correlations, it is found that the Median of the data will give accurate results and average time has a major contribution in radiation measurement., Comment: 3 pages, 12 images, 1 Table

Scintillator detectors electronics is recalibrated against the datasheet given by the manufacturer. Optimal and mutual dependent values of (a) high voltage at PMT (Photomultiplier Tube), (b) amplifier gain, (c) average time to count the radiation particles (set by operator), and (d) number of instances/sample number are estimated. Total 5: two versions of Central Limit Theorem (CLT), (3) industry preferred Pulse Width Saturation, (4) calibration based on MPPC coupled Gamma-ray detector and (5) gross method are used. It is shown that CLT method is the most optimal method to calibrate detector and its respective electronics couple. An inverse modeling-based Computerized Tomography method is used for verification. It is shown that statistically averaging results are more accurate and precise data than mode and median, if the data is not skewed and random number of samples are used during the calibration process. It is also shown that the average time to count the radiation particle is the most important parameter affecting the optimal calibration setting for precision and accurate measurements of gamma radiation., Comment: 13 Page, 8 Fig., Pre-Print Draft