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The Value of Diffusion Weighted MRI in the Detection and Localization of Prostate Cancer among a Sample of Iraqi Patients
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Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad from September 2017 to September 2018. Thin sections axial T2 and DWI sequences were performed for each patient. Two patients were excluded from the study due to poor image quality (motion artefact). Regions with hypointense signal on T2WI and/or restricted lesion in DWI were determined. The ADC values were measured and the results were registered and sent for biopsy correlation. The sensitivity, specifity, accuracy and other parameters were calculated for T2WI and DWI.

Results: The sensitivity and specifity of T2WI in the detection of prostate cancer was about 76.6% and 77% respectively. These improved to 96% and 88.8% by performing the DWI and measuring the ADC value. The mean ADC value was greatly lower in prostatic cancer (about 650x 10-6 mm2 /s) than in normal prostate parenchyma (about 1250 x10-6 mm2 /s) with significant difference between them (p value about 0.04)

Conclusion: In practice, using diffusion weighted MRI sequence and its ADC quantitative measurement greatly increases tumor detection in patients suspicious to have prostatic cancer and should be routinely used when doing pelvic MRI for patients with high clinical suspicion.

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Publication Date
Tue Jul 17 2018
Journal Name
International Journal Of Adaptive Control And Signal Processing
Single channel informed signal separation using artificial-stereophonic mixtures and exemplar-guided matrix factor deconvolution
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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Relationship between serum Nesfatin-1, Adiponectin, Resistin Concentration, and Obesity with Type 2 Diabetes Mellitus
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            Diabetes mellitus caused by insulin resistance is prompted by obesity. Neuropeptide Nesfatin-1 was identified in several organs, including the central nervous system and pancreatic islet cells. Nesfatin-1 peptide appears to be involved in hypothalamic circuits that energy homeostasis and control food intake. Adiponectin is a plasma collagen-like protein produced by adipocytes that have been linked to the development of insulin resistance (IR), diabetes mellitus type 2 (DMT2), and cardiovascular disease (CVD). Resistin was first identified as an adipose tissue–specific hormone that was linked to obesity and diabetes.  The aim of this study was to estimate the relationship between human serum nesfatin-1, adiponect

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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
On semi strongly (E, F)-convex functions and semi strongly (E, F)-convex optimization problems
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Abstract<p>In this paper, a new class of non-convex functions called semi strongly (<italic>E, F</italic>)-convex functions are presented. This class represents a natural extension of semi strongly <italic>E</italic>-convex functions shown in the literature. Different properties of this class of functions are discussed. Optimality properties of constrained optimization problems in which the objective function or the inequality constraints functions are semi strongly (<italic>E, F</italic>)-convex are proved for this class.</p>
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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
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A new features extraction approach is presented based on mathematical form the modify soil ratio (MSR) and skewness for numerous environmental studies. This approach is involved the investigate on the separation of features using frequency band combination by ratio to estimate the quantity of these features, and it is exhibited a particular aspect to determine the shape of features according to the position of brightness values in a digital scenes, especially when the utilizing the skewness. In this research, the marginal probability density function G(MSR) derivation for the MSR index is corrected, that mentioned in several sources including the source (Aim et al.). This index can be used on original input features space for three diffe

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Low Latency UHD Adaptive Video Bitrate Streaming Based on HEVC Encoder Configurations and Http2 Protocol
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      Applying 4K, (Ultra HD) Real-time video streaming via the internet network, with low bitrate and low latency, is the challenge this paper addresses. Compression technology and transfer links are the important elements that influence video quality. So, to deliver video over the internet or another fixed capacity medium, it is essential to compress the video to more controllable bitrates (customarily in the 1-20 Mbps range). In this study, the video quality is examined using the H.265/HEVC compression standard, and the relationship between quality of video and bitrate flow is investigated using various constant rate factors, GOP patterns, quantization parameters, RC-lookahead, and other types of video motion sequences. The ultra

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Mon Mar 01 2021
Journal Name
Desalination And Water Treatment
Extraction model to remove antibiotics from aqueous solution by emulsion and Pickering emulsion liquid membrane
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Publication Date
Sun Oct 06 1996
Journal Name
Iraqi Journal Of Chemistry
Synthesis of new Schiff bases derived from [3-amino-3-C-cyano-3-deoxy-1,2:5,6-di-O-isopropylidene-α-D-allofuranose
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Aromatic Schiff-bases are known to have antibacterial activity, but most of these compounds are sparingly soluble in water. The present work describes the synthesis of new Schiff-bases derived from branched aminosugars. Treatment of 3-Amino-3-Cyano-3-Deoxy-1,2:5,6-Di-O-Isopropylene-α-D-Allofuranose (1) with the aldehydes (2) under reflux in methanol afforded the Schiff-bases (3) in good yields. The new Schiff-bases were in accord with their NMR, IR spectral data and elemental analysis.

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