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The Diagnostic Accuracy of Sonography, With Graded Compression to Image Acute Appendicitis Compared to Histopathologic Results
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Acute appendicitis is the most common surgical abdominal emergency. Its clinical diagnosis remains a challenge to surgeons, so different imaging options were introduced to improve diagnostic accuracy. Among these imaging modality choices, diagnostic medical sonography (DMS) is a simple, easily available, and cost effective clinical tool. The purpose of this study was to assess the accuracy of DMS, in the diagnosis of acute appendicitis compared to the histopathology report, as a gold standard. Between May 2015 and May 2016, 215 patients with suspected appendicitis were examined with DMS. The DMS findings were recorded as positive and negative for acute appendicitis and compared with the histopathological results, as a gold standard. In all, 173 patients were correctly diagnosed as having acute appendicitis by DMS out of 200 cases, with a final histopathologic result. Similarly, DMS revealed 13 normal appendices out of 15 nonappendicitis patients. This demonstrated that DMS has a sensitivity of 86.5%, specificity of 86.6%, positive predictive value of 99.8%, negative predictive value of 32.5%, and overall accuracy of 86.5%. These results suggest that DMS may be an accurate, sensitive, and specific tool for diagnosing acute appendicitis and reducing unnecessary appendectomies. DMS should be considered as a credible imaging modality for diagnosing acute appendicitis.

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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform
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Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Image restoration using regularized inverse filtering and adaptive threshold wavelet denoising
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Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
MR Brain Image Segmentation Using Spatial Fuzzy C- Means Clustering Algorithm
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conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation
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Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

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Publication Date
Wed Jan 01 2020
Journal Name
Modern Sport
Special exercises according to the Dynafoot data and its effect on the force index and the performance of the front straight air flip skill on the ground movements mat device
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Publication Date
Sun Dec 20 2020
Journal Name
International Journal Of Research In Social Sciences And Humanities
THE EFFECT OF MAXIMUM PHYSICAL EXERTION EXERCISES ACCORDING TO THE ANAEROBIC THRESHOLD ON THE DEVELOPMENT OF EXPLOSIVE ABILITY AND THE SKILL OF SHOOTING BY JUMPING HIGH IN FRONT OF HANDBALL FOR YOUTH
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The sports field is one of the fields that are concerned with the various methods and methods because of their positive impact on the development of actual training, the investment of the exerted effort in time, and through the follow-up of the researcher in the field and academic field, I noticed that there is a weakness in explosive ability, which affects performance and skill level during training and competition Therefore, the researcher decided to prepare maximum physical exertion exercises according to the anaerobic threshold as a principle of development in many physical and skill variables because good physical performance leads to reaching the best achievements and since the skill of shooting by jumping high - either constitutes a

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Publication Date
Tue Oct 01 2019
Journal Name
The Journal Of Immunology
AhR Activation Leads to Massive Mobilization of Myeloid-Derived Suppressor Cells with Immunosuppressive Activity through Regulation of CXCR2 and MicroRNA miR-150-5p and miR-543-3p That Target Anti-Inflammatory Genes
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Abstract<p>The compound 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an environmental contaminant, is a potent ligand for aryl hydrocarbon receptor (AhR). In the current study, we made an exciting observation that naive C57BL/6 mice that were exposed i.p. to TCDD showed massive mobilization of myeloid-derived suppressor cells (MDSCs) in the peritoneal cavity. These MDSCs were highly immunosuppressive and attenuated Con A–induced hepatitis upon adoptive transfer. TCDD administration in naive mice also led to induction of several chemokines and cytokines in the peritoneal cavity and serum (CCL2, CCL3, CCL4, CCL11, CXCL1, CXCL2, CXCL5, CXCL9, G-CSF, GM-CSF, VEGF, and M-CSF) and chemokine receptors</p> ... Show More
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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Specific Activities of Natural Radionuclides and Annual Effective Dose Due to the Intake of Some Types of Children Powdered Milk Available in Baghdad Markets
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In this research the specific activity of natural radionuclides 226Ra, 232Th and 40K were determined by sodium iodide enhanced by thallium NaI(TI) detector and assessed the annual effective dose in Dielac 1 and 2 and Nactalia 1 and 2 for children of less than 1 year which are available in Baghdad markets. The specific activity of 40K has the greater value in all the types which is in the range of allowed levels globally that suggested by UNSCEAR. The mean value of annual effective doses were 2.92, 4.005 and 1.6325 mSv/y for 226Ra, 232Th and 40K respectively.

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Building social intelligence scale and applied to a sample at the Deprived and non-Deprived students from their parents at the Secondary stage
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The current research aims to :
•know the level of social intelligence of the sample as a whole .
. •taraf statistically significant differences in social intelligence between disadvantaged and
non-disadvantaged peers .
To achieve these objectives, the selected sample of Talbhalmrahlh medium and specifically
students of the second grade average, were chosen randomly stratified's (360) students
included sex (male, female) and (deprived of the Father and the non-deprived) for the
academic year (2013-2014) for the province of Baghdad on both sides (Rusafa-Karkh (
As applied to them measurements of social intelligence, which is prepared by the researcher,
having achieved _khasaúsma of psychometric (valid and re

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Publication Date
Fri Apr 01 2016
Journal Name
Al–bahith Al–a'alami
Indicators of Mental image among Students of the University of Baghdad about Iraqi Political Parties-(a research based on a master thesis)
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Media studies have focused mostly on the issue of the mental image because the image that is formed in the mind has become not only a photo of a human being and having kept for himself. This image has an outside influence which may sometimes up to the formation of the fate of others and it sometimes includes individuals and groups together.
This study comes in the context of identifying the image of Iraqi political parties among Iraqi university students and the nature of the view that students have in their minds about these parties.
Chapter one includes the problem of the research, the importance of the study, the goals and method used. Chapter two is divided into two sections: section one deals with the concept of the mental i

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