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MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.

Publication Date
Thu Jan 15 2009
Journal Name
Thesis
Infantile Gastroenteritis Multifactorial Disease
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Total no. of patient (100) stool samples were collected, during the period from February to the end of May of 2008, for children under two years old suffering from non-bloody and bloody diarrhea at (Children Welfare Teaching Hospital) in Baghdad. The study evaluates the relationship between etiological agent of diarrhea and sex, age group, type of feeding, presence of blood in stool of the patients. All samples were examined microscopically to identify parasitic agent and serological test for Rotavirus to identify viral infection, also biochemical and serological tested for specimen's culture on different culture media and antibiotic sensitivity test. Results show from 100 cases 64] represents the etiological agent of diarrhea and

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Publication Date
Wed Jun 28 2023
Journal Name
Mathematics
The Impact of Fear on a Harvested Prey–Predator System with Disease in a Prey
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A mathematical eco-epidemiological model consisting of harvested prey–predator system involving fear and disease in the prey population is formulated and studied. The prey population is supposed to be separated into two groups: susceptible and infected. The susceptible prey grows logistically, whereas the infected prey cannot reproduce and instead competes for the environment’s carrying capacity. Furthermore, the disease is transferred through contact from infected to susceptible individuals, and there is no inherited transmission. The existence, positivity, and boundedness of the model’s solution are discussed. The local stability analysis is carried out. The persistence requirements are established. The global behavior of th

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Publication Date
Mon Feb 22 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
MRI images series segmentation using the geodesic deformable model
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Publication Date
Mon Feb 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Satellite Images Fusion Using Mapped Wavelet Transform Through PCA
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In this paper a new fusion method is proposed to fuse multiple satellite images that are acquired through different electromagnetic spectrum ranges to produce a single gray scale image. The proposed method based on desecrate wavelet transform using pyramid and packet bases, the fusion process preformed using two different fusion rules, where the low frequency part is remapped through the use of PCA analysis basing on covariance matrix and correlation matrix, and the high frequency part is fused using different fusion rules (adding, selecting the higher, replacement), then the restored image is obtained by applying the inverse desecrate wavelet transform. The experimental results show the validity of the proposed fusion method to fuse suc

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Publication Date
Sat Feb 27 2021
Journal Name
Iraqi Journal Of Science
Automatic Pectoral Muscles Detection and Removal in Mammogram Images
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The main aim of the Computer-Aided Detection/Diagnosis system is to assist the radiologists in examining the digital mammograms. Digital mammogram is the most popular screening technique for early detection of breast cancer. One of the problems in breast mammogram analysis is the presence of pectoral muscles region with high intensity in the upper right or left side of most Media-Lateral Oblique views of mammogram images. Therefore, it is important to remove this pectoral muscle from the image for
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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
Hybrid Images Compression and Transmitted Using MC-CDMA System
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In this paper, the combined source coding with Multi Carrier Code Division Multiple Access (MC-CDMA) system is proposed, where the transmission of the compressed image produced from source coding through Additive White Gaussian Noise (AWGN) channel for a single user and multi users. In which the (MC-CDMA) system removes Inter Symbol Interference (ISI) and Inter Carrier Interference (ICI). The hybrid compression system of Discrete Cosine Transform (DCT) and predictive coding (PC) technique are integrated as a source coding. The simulation results indicates that the transmission system of a single user was much better than the transmission system of multi users. When the number of users increased, the Bit Error Rate (BER) increased. For a

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Publication Date
Tue Apr 02 2024
Journal Name
Advances In Systems Science And Applications
A New Face Swap Detection Technique for Digital Images
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Publication Date
Sat Jul 01 2023
Journal Name
International Journal Of Computing And Digital Systems
Human Identification Based on SIFT Features of Hand Image
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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Synthesis and Characterization of Derivatives Based on 4, - Dimercaptobiphenyl
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Starting from 4, - Dimercaptobiphenyl, a variety of phenolic Schiff bases (methylolic, etheric, epoxy) derivatives have been synthesized. All proposed structure were supported by FTIR, 1H-NMR, 13C-NMR Elemental analysis all analysis were performed in center of consultation in Jordan Universty.

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
Iris Identification Based on the Fusion of Multiple Methods
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Iris recognition occupies an important rank among the biometric types of approaches as a result of its accuracy and efficiency. The aim of this paper is to suggest a developed system for iris identification based on the fusion of scale invariant feature transforms (SIFT) along with local binary patterns of features extraction. Several steps have been applied. Firstly, any image type was converted to  grayscale. Secondly, localization of the iris was achieved using circular Hough transform. Thirdly, the normalization to convert the polar value to Cartesian using Daugman’s rubber sheet models, followed by histogram equalization to enhance the iris region. Finally, the features were extracted by utilizing the scale invariant feature

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