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.
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Horizontal wells are of great interest to the petroleum industry today because they provide an attractive means for improving both production rate and recovery efficiency. The great improvements in drilling technology make it possible to drill horizontal wells with complex trajectories and extended for significant depths.
The aim of this paper is to present the design aspects of horizontal well. Well design aspects include selection of bit and casing sizes, detection of setting depths and drilling fluid density, casing, hydraulics, well profile, and construction of drillstring simulator. An Iraqi oil field (Ajeel field) is selected for designing horizontal well to increase the productivity. Short radius horizontal well is suggested fo
This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ
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Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of
... Show MoreIn this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F
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Idiomatic expressions in Russian journalism make one important borrowed means for making a dialogue with the receiver's intellect in so far as it has the distinct feature of having clarity and exactness of meaning. The meaning is seen as a shortcut for covering a series of concepts and details so as to arrive at the intended meaning. This is done by stimulating the reader by the use of certain clear idioms. The use of such idioms in a journalistic text is not for a linguistic purpose only, but it is a cultural and social phenomenon reflecting the type of current changes in the society and it aims at discoursing with the reader's mind. This paper is a practi
... Show MoreThis paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining
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