Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, coronal plane, and sagittal plane. Three different thresholds, which are based on texture features: mean, energy and entropy, are obtained automatically. This allowed to accurately separating the MRI slice into normal and abnormal one. However, the abnormality detection contained some normal blocks assigned wrongly as abnormal and vice versa. This problem is surmounted by applying the fine-tuning mechanism. Finally, the MRI slice abnormality detection is achieved by selecting the abnormal slices along its tumour region (Region of Interest-ROI).
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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In this paper, third order non-polynomial spline function is used to solve 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of this method, and to compare the computed results with other known methods.
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In this research, the electrical characteristics of glow discharge plasma were studied. Glow discharge plasma generated in a home-made DC magnetron sputtering system, and a DC-power supply of high voltage as input to the discharge electrodes were both utilized. The distance between two electrodes is 4cm. The gas used to produce plasma is argon gas which flows inside the chamber at a rate of 40 sccm. The influence of work function for different target materials (gold, copper, and silver), - 5cm in diameter and around 1mm thickness - different working pressures, and different applied voltages on electrical characteristics (discharge current, discharge potential, and Paschen’s curve) were studied. The results showed that the discharge cur
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A direct, sensitive and efficient spectrophotometric method for the determination of nitrofurantoin
drug (NIT) in pure as well as in dosage form (capsules) was described. The suggested method was
based on reduction NIT drug using Zn/HCl and then coupling with 3-methyl-2-benzothiazolinone
hydrazone hydrochloride (MBTH) in the presence of ammonium ceric sulfate. Spectrophotometric
measurement was established by recording the absorbance of the green colored product at 610 nm.
Using the optimized reaction conditions, beer’s law was obeyed in the range of 0.5-30 μg/mL, with
good correlation coefficient of 0.9998 and limits of detection and quantitation of 0.163 and 0.544
μg/mL, respectively. The accuracy and
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Several million tons of solid waste are produced each year as a result of construction and demolition activities around the world, and brick waste is one of the most widely wastes. Recently, there has been growing number in studies that conducted on using of recycling brick waste (RBW) to produce environmentally friendly concrete. The use of brick waste (BW) as potential partial cement or aggregate replacement materials is summarized in this review where the performance is discussed in the form of the mechanical strength and properties that related to durability of concrete. It was found that, because the pozzolanic activity of clay brick powder, it can be utilized as substitute for cement in replacement level up t
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Peer-Reviewed Journal
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