Background: The figure for the clinical application of computed tomography have been increased significantly in oral and maxillofacial field that supply the dentists with sufficient data enables them to play a main role in screening osteoporosis, therefore Hounsfield units of mandibular computed tomography view used as a main indicator to predict general skeleton osteoporosis and fracture risk factor. Material and Methods: Thirty subjects (7 males &23 females) with a mean age of (60.1) years underwent computed tomographic scanning for different diagnostic assessment in head and neck region. The mandibular bone quality of them were determined through Hounsfield units of CT scan images and were correlated with the bone mineral density values obtained from t-scores of lumbar spine using dual x-ray absorptiometry scans (DEXA). Results: There was a highly signifi¬cant positive correlation [p-value 0.000 (HS)] of bone mineral density that measured by t-score of dual x-ray absorptiometrical scan and Hounsfield units with very strong relation in measuring the bone density (r test) = 0.969, this close relation lead to predict osteoporosity and the chance of fracture occurrence using a statistical equation that classified the patients as osteoporotic. Conclusion: Hounsfield units obtained from computed tomography scans that are made for any purposes can provide an alternative clinical parameter to predict osteoporosis at no additional cost to the patient and no additional radiation.
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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Background: The styloid process is a cylindrical bone (protrusion). It situated above the common carotid artery between the external and internal branches immediately proximal to the internal jugular vein and facial nerves. The styloid process varies in length also it may be absent as well as elongated. Classically, an elongated styloid process and calcified of stylohyoid ligament causes Eagle’s syndrome. The aim of this study was to examine the styloid process using 3 dimensional multi-detector computed tomography (3D-MDCT) to detect the presence of Eagle’s syndrome that causes severe headache and migraine. Materials and methods: One hundred patients with severe headache and migraine were exposed to 3D- multi-detector CT with special
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In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement. The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.
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Chest X-rays have long been used to diagnose pneumothorax. In trauma patients, chest ultrasonography combined with chest CT may be a safer, faster, and more accurate approach. This could lead to better and quicker management of traumatic pneumothorax, as well as enhanced patient safety and clinical results.
The purpose of this study was to assess the efficacy and utility of bedside US chest in identifying traumatic pneumothorax and also its capacity to estimate the extent of the lesion in comparison to the gold standard modality chest computed tomography.
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