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Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when diagnosing a tissue sample. Small, unnoticeable changes in pixel density may indicate the beginning of cancer or tear tissue in the early stages. These details even expert pathologists might miss. Artificial intelligence (A.I.) and D.L. revolutionized radiology by enhancing efficiency and accuracy of both interpretative and non-interpretive jobs. When you look at AI applications, you should think about how they might work. Convolutional Neural Network (C.N.N.) is a part of D.L. that can be used to diagnose knee problems. There are existing algorithms that can detect and categorize cartilage lesions, meniscus tears on M.R.I., offer an automated quantitative evaluation of healing, and forecast who is most likely to have recurring meniscus tears based on radiographs.

Publication Date
Tue Sep 21 2021
Journal Name
Earth Resources And Environmental Remote Sensing/gis Applications Xii
Investigating the old city of Babylon: tracing buried structural history based on photogrammetry and integrated approaches
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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors
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In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes est

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Two Spectrophotometric Methods Based on Diazotization Coupling Reaction for Determination of Genistein in Pure and Supplement
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      Genistein (GEN) is one of the predominant dietary isoflavones found in legumes such as soybeans. Genistein has been recommended as an osteoporosis treatment for postmenopausal women and elderly men, with the intention of reducing cardiovascular disease and hormone-dependent malignancies. Therefore, two sensitive and simple methods for quantifying it in the supplements preparation were developed.The first method (A) comprised employing the surfactant Triton X-114 to extract the result of the diazotization reaction with 4-Aminoacetophenone(4AMA) utilizing a cloud point extraction technique. The product was extracted using micelles of a non-ionic surfactant (TritonX-114) and then spectrophotometrically detected at a specified wa

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Improving the Accuracy of Handheld GPS Receivers Based on NMEA File Generating and Least Squares Adjustment
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This study aims to improve the quality of satellites signals in addition to increase accuracy level delivered from handheld GPS data by building up a program to read and decode data of handheld GPS. Where, the NMEA protocol file, which stands for the National Marine Electronics Association, was generated from handheld GPS receivers in real time using in-house design program. The NMEA protocol file provides ability to choose points positions with best status level of satellites such as number of visible satellite, satellite geometry, and GPS mode, which are defined as accuracy factors. In addition to fix signal quality, least squares technique was adopted in this study to minimize the residuals of GPS observations and enh

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Publication Date
Mon Jan 31 2022
Journal Name
Iraqi Journal Of Science
Synthesis and Characterization of Several New Copolymers Based on Maleimides Bearing 1, 3, 4-Oxadiazole Moiety
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A series of new copolyimides containing pendant 1,3,4-oxadiazole moiety were synthesized via multisteps. In the first step five N-(5-substituted-1,3,4-oxadiazole-2-yl)maleamic acids were prepared via reaction of maleic anhydride with 2-amino-5-substituted-1,3,4-oxadiazoles. The obtained amic acids were dehydrated in the second step affording the corresponding N-(5-substituted-1,3,4-oxadiazole-2-yl) maleimides. In the third step the newly synthesized maleimides were introduced successfully in free radical copolymerization reaction with four vinylic monomers including acrylo nitrile, methacrylonitrile, methyl acrylate and methyl meth acrylate respectively producing twelve new copolymers having different physical properties which may serve

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Publication Date
Mon Jan 01 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
Calculating land surface temperature of South Baghdad by the using Landsat 8 images
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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Using Statistical Methods to Increase the Contrast Level in Digital Images
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This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.

 

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Hybrid Techniques with Support Vector Machine for Improving Artifact Ultrasound Images
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     The most common artifacts in ultrasound (US) imaging are reverberation and comet-tail. These are multiple reflection echoing the interface that causing them, and result in ghost echoes in the ultrasound image. A method to reduce these unwanted artifacts using a Otsu thresholding to find region of interest (reflection echoes) and output applied to median filter to remove noise. The developed method significantly reduced the magnitude of the reverberation and comet-tail artifacts. Support Vector Machine (SVM) algorithm is most suitable for hyperplane differentiate. For that, we use image enhancement, extraction of feature, region of interest, Otsu thresholding, and finally classification image datasets to normal or abnormal image.

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Economics And Administrative Sciences (jeas)
Using Statistical Methods to Increase the Contrast Level in Digital Images
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This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods