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).
The present study aimed at shed light on the association between HLA-class I antigens (A, B and Cw) and brain tumours (meningioma and glioma) in the basis of their individual frequencies or two-locus association A total of 52 brain tumour patients were enrolled in this study, with an age range of 7-68 years. The patients were divided into two clinical groups; meningioma (20 cases) and glioma (22 cases), while the remaining 10 cases represented other types of brain tumour. Control samples included 47 Iraqi Arab apparently healthy blood volunteers, with an age range of 15-50 year. Three HLA antigens showed a significant increased frequency in total patients as compared to controls. They were B13 (34.6 vs. 6.5%), B40 (15.4 vs. 2.2%) and Cw3
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(1) Background: Sleeping disorders are frequently reported following traumatic brain injury (TBI). Different forms of sleeping disorders have been reported, such as sleepiness, insomnia, changes in sleeping latency, and others. (2) Methods: A case-control study with 62 patients who were victims of mild or moderate TBI with previous admissions to Iraqi tertiary neurosurgical centers were enrolled as the first group, and 158 patients with no history of trauma were considered as the control. All were 18 years of age or older, and the severity of the trauma and sleep disorders was assessed. The Pittsburgh sleep quality index was used to assess sleep disorders with average need for sleep per day and average sleep latency were assessed in
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Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm
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Present investigation aimed to study plasma BNP hormone estimation as predictor of brain stroke and neurocognitive in relative with other limitations in CKD patient. The case control experimental study was conducted on CKD patient at Yarmuk Hospital at Baghdad Province, Iraq from February to April 2020. The results showed that there were significant variances (P< 0.05) between CKD patients and control group, there was significant increase in BNP hormone and cystatin-C levels at patient, while ihematological parameters were significantly decreased. The parameters of lipid profile were significantly increased (P<0.05). The result revealed that there was relationship between BNP hormone level and CKD. This support that BNP level is related wit
... Show MoreWith the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp
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Nearly, in the middle of 1970s the split-brain theory became the only theory that explains human creativity used in all fine art and art education schools. In fact, this theory- which appeared for first time in the middle of 1940s – faced many radical changes including its concepts and structures, and these changes affected both teaching art and art criticism. To update people awareness within art field of study, this paper reviews the split-brain theory and its relationship with teaching art from its appearance to its decay in 2013 and after.
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In this article, a new efficient approach is presented to solve a type of partial differential equations, such (2+1)-dimensional differential equations non-linear, and nonhomogeneous. The procedure of the new approach is suggested to solve important types of differential equations and get accurate analytic solutions i.e., exact solutions. The effectiveness of the suggested approach based on its properties compared with other approaches has been used to solve this type of differential equations such as the Adomain decomposition method, homotopy perturbation method, homotopy analysis method, and variation iteration method. The advantage of the present method has been illustrated by some examples.
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This paper aims to evaluate the reliability analysis for steel beam which represented by the probability of Failure and reliability index. Monte Carlo Simulation Method (MCSM) and First Order Reliability Method (FORM) will be used to achieve this issue. These methods need two samples for each behavior that want to study; the first sample for resistance (carrying capacity R), and second for load effect (Q) which are parameters for a limit state function. Monte Carlo method has been adopted to generate these samples dependent on the randomness and uncertainties in variables. The variables that consider are beam cross-section dimensions, material property, beam length, yield stress, and applied loads. Matlab software has be
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