Background: Since its introduction to musculoskeletal imaging in the early 1980, magnetic resonance imaging (MRI) has revolutionized diagnostic imaging of the knee. It is therefore become the examination of choice in the evaluation of internal joint structures of the knee like menisci, cruciate ligaments, and articular cartilage.Objectives: to describe the MRI finding in various knee injuries.Patients and methods: A cross sectional study was done on 130 patients with history of knee injury in MRI unit at institute of radiology and al-Shaheed Ghazi Al-Hariri Hospital in medical city complex - Baghdad, from October 2011 to February 2013 includes 103 men, 27 women; the mean age was 33.86 years. MR imaging studies of the knee performed using a 1.5 T MR system. The sequences included coronal and sagittal PD, sagittal T2 FSE, fat suppressed T2 FSE, STIR axial and coronal. Knee MR studies were obtained to evaluate ligament, menisci, articular surface and bone pathologies of knee injuries.Results: MR images were normal in 15 patients; it was positive for meniscal tears in 59 patients and maximum involvement was in the medial meniscus and the posteriorhorn. These tears were classified into grade 1 (28.8%), grade 2 (11.5%), grade 3 (53.9%) and grade 4 (5.8%). Ligament tears were seen in 70 patients. Secondary signs associated with ligament tears were also assessed.Conclusions: MRI is an accurate, non-invasive technique for examination of the soft tissues and osseous structures of the knee. It has great capability in diagnosing meniscal tears and classifying them into grades and types, which would avoid unnecessary arthroscopic examination. It is a very good modality to diagnose complete tears of the anterior cruciate ligament (ACL).maging, meniscus
We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
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The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s
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ABSTRACT Pulmonary alveolar microlithiasis is rare infiltrative pulmonary disease characterized by intra-alveoli deposition of microliths. We present a familial case of an adult female with complaint of progressive shortness of breath on exertion. Chest radiograph showed innumerable tiny dense nodules, diffusely involving both lungs mainly the lower zones. High-resolution CT scan illustrated widespread intra-alveolar microliths, diffuse ground-glass attenuation areas and septal thickening predominantly in the basal regions. Chest radiograph is all that is needed for the diagnosis of this case but CT scan was done to demonstrate the extent and severity of this disease
Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use
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Osteoarthritis is the most prevalent arthritic disease and a leading cause of disability. The pathogenesis of osteoarthritis involves multiple etiologies, including variable degree of synovial inflammation. Metformin and pioglitazone could potentially reduce the levels and activity of inflammatory mediators. This may consider as a new therapeutic approach added to the current used drugs in an attempt to decrease the pain, inflammation, and improve daily activity and quality of life in patients with knee osteoarthritis.
This study designed to evaluate the clinical utility of using metformin or pioglitazone as anti-inflammatory agents in combination with non-steroidal anti-inflammatory drugs (NSAID) of selective type of cyclooxygen
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CADTEL software was developed to provide the simplest and most versatile computing resource that a wide range of skilled researchers and designers can use. In this paper, a development on this program, relying on sixteen mathematical models, produced a new version of CADTEL software package which focuses on the optimum conditions of Scherzer imaging for round electron magnetic lenses.. These models depend on synthesis procedure which is mainly designed to work with the inverse design problem, and represent the axial magnetic flux density of desirable electron magnetic lens which can be proposed or selected , using the four (zero, low, high, infinite) magnification states. The p
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Magnetic Resonance Imaging (MRI) is a medical indicative test utilized for taking images of the tissue points of interest of the human body. During image acquisition, MRI images can be damaged by many noise signals such as impulse noise. One reason for this noise may be a sharp or sudden disturbance in the image signal. The removal of impulse noise is one of the real difficulties. As of late, numerous image de-noising methods were produced for removing the impulse noise from images. Comparative analysis of known and modern methods of median filter family is presented in this paper. These filters can be categorized as follows: Standard Median Filter; Adaptive Median Filter; Progressive Switching Median Filter; Noise Adaptive Fuz
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Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images
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