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Estimation intensity radiation of chest X-ray (CXR) with application
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In this research we assumed that the number of emissions by time (𝑡) of radiation particles is distributed poisson distribution with parameter (𝑡), where  < 0 is the intensity of radiation. We conclude that the time of the first emission is distributed exponentially with parameter 𝜃, while the time of the k-th emission (𝑘 = 2,3,4, … . . ) is gamma distributed with parameters (𝑘, 𝜃), we used a real data to show that the Bayes estimator 𝜃 ∗ for 𝜃 is more efficient than 𝜃̂, the maximum likelihood estimator for 𝜃 by using the derived variances of both estimators as a statistical indicator for efficiency

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Publication Date
Sat Jan 01 2011
Journal Name
Iraqi Journal Of Physics
Radiation contrast improvement by suitable choice of x-ray radiation spectrum
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Different bremsstrahlung spectra from tungsten anode x-ray tube generated at 30, 40 and 50 kV have been examined theoretically and experimentally for an attempt to find a most suitable spectrum to radiograph a test object of 0.01 cm thickness of Cu and Ag. The high contrast using this suitable spectrum is demonstrated and the possible effects of fluorescent radiation are discussed.

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Sun Oct 02 2016
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Evaluation of Ionizing Radiation Protection among Radiation Workers in X-ray departments in Erbil City
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Background: Ionizing radiations are hazardous agents in the workplace, since all forms of ionizing radiation produce some type of injury that is incurable. Therefore, protection against ionizing radiation exposure can play an important role in the health of workers.
Objectives: is to evaluate the application of radiation protection among radiation workers at X-ray department in Erbil hospitals.
Patients and methods: Six hospitals (General and Private) were visited. Samples of 110 were randomly selected among 135 radiation workers, 47 (42.3%) female and 63 (57.3%) male Data was collected through structured questionnaires. The surveyed data was coded and analyzed by using MS Excel software, and SPSS 18 f

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Publication Date
Wed Apr 01 2009
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The Value of the chest X-Ray for diagnosing left ventricular Dysfunction
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Background: The use of the chest x-ray measurements which includes the cardiothoracic ratio(C-T) and frontal area (FA) of the heart by the CXR are useful measures for primary assessment of the cardiac dysfunction.
Patients and Methods: A Prospective study was done from the 1st of January 2005 to the 1st of October in the same year on a 120 consecutive patients who have been admitted for coronary and L.V angiogram at IBN-AL-BITAR hospital. The C-T ratio and the frontal area were measured.
Results: The study comprised 120 subjects who were admitted for coronary and L.V angiogram for diagnostic reasons. 89subjects (74.2%) are male and 31subjects (25.8%) are female .17(14%) subjects have left ventricular d

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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Deep Convolutional Neural Network Architecture to Detect COVID-19 from Chest X-Ray Images
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      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

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Publication Date
Sun Oct 27 2019
Journal Name
Iraqi Journal Of Science
Determination of Radiation Dose from Routine X-ray Examination at Three Selected Hospitals in AlNajaf, Iraq
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People who undertaken different X-ray examinations are already exposed to ionizing radiation which causes biological effects. Therefore assessing the patient radiation dose is a prerequisite element in optimizing the X-ray practice and to avoid the unnecessary radiation dose. The aim of this research is to assess the skin radiation dose for those patients who undertaking routine X-ray examinations in selected three hospitals in Al Najaf city.

     Three X-ray units were involved in this experimental study; these were belonging to three hospitals in Al Najaf city-Iraq, namely Al-Sadder teaching hospital, Al-Hakeem general hospital and Al-Zahraa hospital. Data of exposure parameters (tube potential (kVp), tube c

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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Automatic Computer Aided Diagnostic for COVID-19 Based on Chest X-Ray Image and Particle Swarm Intelligence
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Publication Date
Wed Jan 01 2020
Journal Name
Studies In Big Data
COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor
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Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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