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 research aimed to prepare a measure to evaluate the academic achievement of graduates working in the field of physical education from their point of view, to identify the extent to which graduating students benefit from the curriculum of the College of Physical Education and Sports Sciences, University of Baghdad/Al-Jadriya, and to identify the impact of academic subjects in the practical and theoretical fields. The researchers used the descriptive approach in the research procedures as it is an appropriate approach in achieving the research objectives. The following questions are: What are the academic subjects that have the most impact on graduating students? What are the academic subjects that have the least impact on the are
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Abstract
The role of the independent variable and human resources capabilities was the role of the adopted variable. The aim of the research is to identify the level of participation in the knowledge of the organization through human resources and the rigorous scientific investigation to develop new mechanisms of action that help To manage the organization in the implementation of its mission and achieve its main objectives that have been found for it is to encourage the work of scientific research and maintain the preservation of its continuity to increase the competencies of knowledge, technical and skill to form a future workforce qualified to work In the sectors of society.
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The aim of this study to conduct the effects of fimbrial and lipopolysacchride (LPS) immunization is on the pathohistological changes in rabbits, Fifteen rabbits of both sexes (Weight 1500-2000 gm) divided into three groups (5 animals of each group). The first group was immunized by 1ml (200µg /animal) of fimbrial subcutaneously the second group gave 1 ml ( 200 µg /animal) LPS while the third group was left as negative control group that injected 1 ml phosphate buffer control subcutaneously. First and second groups recived the same dose after two weeks give as booster dose. All animals challenged after 5 weeks of immunization by5X107CFU/ml Proteus vulgaris intra peritoneally .After 7 days from challenge all the animals, sacrificed for hi
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The present work describes guggul as a novel carrier for some anti-inflammatory drugs. Guggulusomes containing different concentration of guggul with aceclofenac were prepared by sonication method and characterized for vesicle shape, size, size-distribution, pH, viscosity, spread ability, homogeneity, and accelerated stability in-vitro drug permeation through mouse skin. The vesicles exhibited an entrapment efficiency of 93.2 ± 12%, vesicle size of 0.769 ± 3μm and a zeta potential of - 6.21mV. In vitro drug release was analyzed using Franz’s diffusion cells. The cumulative release of the guggulusomes gel (G2) was 75.8% in 18 hrs, which is greater than that all the gel formulation. The stability profile of prepare
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The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame
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The present work provides theoretical investigation of laser photoacoustic one dimensional imaging to detect a blood vessel or tumor embedded within normal tissue. The key task in photoacoustic imaging is to have acoustic signal that help to determine the size and location of the target object inside normal tissue. The analytical simulation used a spherical wave model representing target object (blood vessel or tumor) inside normal tissue. A computer program in MATLAB environment has been written to realize this simulation. This model generates time resolved acoustic wave signal that include both expansion and contraction parts of the wave. The photoacoustic signal from the target object is simulated for a range of laser pulse duration 1
... Show MorePhotoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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