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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
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Sun Sep 01 2013
Journal Name
2013 Ieee International Conference On Circuits And Systems (iccas)
Improved undetected error probability model for JTEC and JTEC-SQED coding schemes
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The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding

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Publication Date
Wed Dec 08 2021
Journal Name
Scientific Reports
Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions
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Abstract<p>Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading to blindness. Computer-Aided Diagnosis systems play an essential role in detecting features in fundus images. Fundus images may include blood vessels, exudates, micro-aneurysm, hemorrhages, and neovascularization. In this paper, our model combines automatic detection for the diabetic retinopathy classification with localization methods depending on weakly-supervised learning. The model has four stages; in stage one, various preprocessing techniques are app</p> ... Show More
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Publication Date
Tue Sep 21 2021
Journal Name
Journal Of Healthcare Engineering
Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGs
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Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent

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Publication Date
Fri Dec 24 2021
Journal Name
Journal Of Engineering Science And Technology. Journal Of Engineering Science And Technology
Grey-Level Image Compression Using 1-D Polynomial and Hybrid Encoding Techniques
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Publication Date
Mon Jan 01 2018
Journal Name
Opcion
Fast-slow thinking and its relationship to cognitive failure At university students
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Publication Date
Fri Jul 01 2016
Journal Name
Composite Structures
Bond behaviour between CFRP laminates and steel members under different loading rates
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Carbon fibre reinforced polymers are widely used to strengthen steel structural elements. These structural elements are normally subjected to static, dynamic and fatigue loadings during their life-time. A number of studies have focused on the characteristics of CFRP sheets bonded to steel members under static, dynamic and fatigue loadings. However, there is a gap in understanding the bonding behaviour between CFRP laminates and steel members under impact loading. This paper shows the effect of different load rates from quasi-static to 300 × 103 mm/min on this bond. Two types of CFRP laminate, CFK 150/2000 and CFK 200/2000, were used to strengthen steel joints using Araldite 420 epoxy. The results show a significant bond strength enhancemen

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Publication Date
Wed Jun 06 2001
Journal Name
مجلة العلوم الاقتصادية والادارية
Double cross-over and cross-over with extra period designs -comparative study-
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The goal of the research is to find the optimization in the test of the appropriate cross-over design for the experiment that the researcher is carrying out (under assumption that there are carry-over effects of the treatments) to posterior periods after the application period (which is often assumed to be the first period). The comparison between the double cross-over design and the cross-over design with extra period. The similarities and differences between the two designs were studied by measuring the Relative Efficiency (RE) of the experiment.

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Engineering
Crack Growth Behavior through Wall Pipes under Impact Loading And Moisten Environment
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This search concerns study the crack growth in the wall of pipes made of low carbon steel under the impact load and using the effect of moisture (rate of moisture 50%). The environmental conditions were controlled using high accuracy digital control with sensors. The pipe has a crack already. The test was performed and on two type of specimens, one has a length of 100cm and other have length 50cm. The results were, when the humidity was applied to the pipe, the crack would enhance to grow (i.e. the number of cycles needed to grow the crack will reduce). In addition, when the test performed on the specimens of length 50cm the number of cycles needed to grow the crack is increased due to the effect of bending stress on the

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Zinc Oxide Hydrogen Sulfide Removal Catalyst/ Preparation, Activity Test and Kinetic Study
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Hydrogen sulfide removal catalyst was prepared chemically by precipitation of zinc bicarbonate at a controlled pH. The physical and chemical catalyst characterization properties were investigated. The catalyst was tested for its activity in adsorption of H2S using a plant that generates the H2S from naphtha hydrodesulphurization and a unit for the adsorption of H2S. The results comparison between the prepared and commercial catalysts revealed that the chemical method can be used to prepare the catalyst with a very good activity.

It has observed that the hydrogen sulfide removal over zinc oxide catalyst follows first order reaction kinetics with activation energy of 19.26 kJ/mole and enthalpy and e

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