Objectives: Small field of view gamma detection and imaging technologies for monitoring in vivo tracer uptake are rapidly expanding and being introduced for bed-side imaging and image guided surgical procedures. The Hybrid Gamma Camera (HGC) has been developed to enhance the localization of targeted radiopharmaceuticals during surgical procedures; for example in sentinel lymph node (SLN) biopsies and for bed-side imaging in procedures such as lacrimal drainage imaging and thyroid scanning. In this study, a prototype anthropomorphic head and neck phantom has been designed, constructed, and evaluated using representative modelled medical scenarios to study the capability of the HGC to detect SLNs and image small organs. Methods: An anthropomorphic head and neck phantom has been designed to mimic the adult head and neck including some internal organs and tissues of interest, such as the thyroid gland and sentinel lymph nodes. The design of the head and neck phantom included an adjustable inner jig holding the simulated SLNs and thyroid gland. The simulated thyroid gland was designed and 3D printed taking into consideration the size and the shape of a healthy adult thyroid gland. The inner sealed space of the thyroid was filled with 15MBq of 99mTc through two upper filling valves. Sealed micro-tubes (0.2ml) have been employed to simulate SLNs containing various 99mTc activity concentrations ranging between 0.1MBq and 1MBq, and can be positioned at any desired place in the head and neck region. An active background was simulated through mixing 10MBq of 99mTc solution with the water used to fill the outer shell of the head and neck phantom. Results: The head and neck phantom was employed to simulate a situation where there are four SLNs distributed at two different vertical levels and at two depths within the neck. Contrast to noise ratio (CNR) calculations were performed for the detected SLNs at an 80mm distance between both pinhole collimators (i.e. 0.5mm and 1.0mm diameters) and the surface of the head and neck phantom with a 100s acquisition time. The recorded CNR values for the simulated SLNs are higher when the HGC was fitted with the 1.0mm diameter pinhole collimator. For instance, the recorded CNR values for the superficially simulated SLN containing 0.1MBq of 99mTc using 0.5mm and 1.0mm diameter pinhole collimators are 6.48 and 16.42, respectively (~87% difference). The anatomical context provided by the hybrid imaging aided the localization process of radioactivity accumulation in simulated SLNs. Gamma and hybrid optical images were acquired using the HGC with both available pinhole collimators for the simulated thyroid gland. The thyroid images produced varied in terms of spatial resolution and detectability. The count profiles through the middle of the simulated thyroid gland images provided by both pinhole collimators were obtained. The HGC could clearly differentiate the individual peaks of both thyroid lobes in the gamma image produced by the 0.5mm pinhole collimator. In contrast, the recorded count profile for the acquired image using the 1.0mm diameter pinhole collimator showed broader peaks for both lobes, reflecting the degradation of the spatial resolution with increasing the diameter of the pinhole collimator. Conclusion: The capability of the HGC has been evaluated utilizing a prototype anthropomorphic head and neck phantom, and the gamma and hybrid images obtained demonstrate that it is ideally suited for intraoperative SLNs detection and small organ imaging. The standardization of test phantoms and protocols for SFOV portable gamma systems will provide an opportunity to collect data across various medical centers and research groups. Moreover, it will provide a technical baseline for researchers and clinical practitioners to consider when assessing their SFOV gamma imaging systems. The anthropomorphic head and neck phantom described is cost effective, reproducible, flexible and anatomically representative.
The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the
... Show MoreThis paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).
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The Local manufacturing scanning gamma system designed in Tuwaitha site for nondestructive assay method of radioactive waste drums, where it consist of two main parts with their belongings for controlling the of detector and drum movements up-down and rotation respectively. The volume of the used drum is 220 L with 85 cm height. The drum filled with Portland cement. Six cylindrical holes were made within cement drum and distributed in radial arrangement.The152Eu source inserted in these holes individually, to measure the average angular count rate of gamma radiation. The full energy efficiency value for geometry of drum and detector is computed for thirteen photo peaks. The average efficiency represented by the curve of these peaks indic
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce
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A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
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The present study aims to identifying the effect of Eurygaster integriceps infection on the quality features of the local wheat varity IBA 99. The result revealed significant decrease in the percentage of protein of infected wheat at (4, 5)% compared to sound wheat values for the sound wheat were (10.9%) whereas those for the infected wheat were(9.0, 8.4 )% also the result revealed significant increased in the percentage of ash in the infected wheat flour. The result showed significant decrease in the percentage of wet and dry gluten in the infected wheat by sun bug at the rate of (2, 3, 4, 5)% compared to sound wheat value (27, 9% and 25, 23, 22, 22, 20%) for wet gluten and (8.2, 7.8, 7, 7.2, 6%) for dry glutin . The value of sedimentati
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The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul
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Abstract Candida albicans is a commensal fungal pathogen that grows in yeast and hyphal forms in the human gut. C. albicans causes mucosal and cutaneous diseases that can result in significant mortality following systematic infections and it also exhibits drug resistance. Zebrafish have been an excellent model to investigate C. albicans infections because of their transparency and the availability of many transgenic lines. However, there is a limitation in using zebrafish as a model because the fish embryos cannot survive at 37°C therefore it is not suitable for studying Candida infections at physiological relevant human body temperature. In this thesis, the normal embryonic development of Arabian killifish (A. dispar) is investigated, rev
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