Preferred Language
Articles
/
lRfgPo8BVTCNdQwCGGXF
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
...Show More Authors

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
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
...Show More Authors

Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Mon Apr 01 2013
Journal Name
International Journal Of Electrical, Electronics And Telecommunication Engineering
Performance Analysis of xPON Network for Different Queuing Models
...Show More Authors

Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

... Show More
View Publication Preview PDF
Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
...Show More Authors

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Calculating Surface Roughness for a Large Scale SEM Images by Mean of Image Processing
...Show More Authors

View Publication
Scopus (25)
Crossref (26)
Scopus Clarivate Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Advances In Computational Intelligence And Robotics
Groupwise Non-Rigid Image Alignment Using Few Parameters: Registration of Facial and Medical Images
...Show More Authors

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

... Show More
View Publication
Publication Date
Sat Nov 30 2019
Journal Name
Journal Of Engineering And Applied Sciences
Distribution of Land Surface Temperatures from Satellite Images for Al-Hammar Marshes In Iraq
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Thu Dec 01 2016
Journal Name
International Journal Of Scientific Research
Anatomical differences of Cerebellar vermismeasurement values in healthy adult men andwomen using MRI images
...Show More Authors

Background: e cerebellum is divided into two hemispheres and contains a narrow midline zone called thevermis. A set of large folds are conventionally used to divide the overall structure into ten smaller "lobules". evermis receives fibres from the trunk and proximal portions of limbs, But the question is that does the cerebellum have the same measurementvalues in males and females of the same age?Material and method: e present study used 80 sectional brain MRI images (40: males, 40: females); 35-50 years old as indices of size for thevermian structures of the Cerebellum. is middle age group was taken because as known generally it could be neither an age of growth as inthe young nor of atrophy as in old individuals. e aim rega

... Show More
View Publication Preview PDF
Publication Date
Thu Mar 25 2021
Journal Name
International Journal For Research In Applied Sciences And Biotechnology
Review Article: Defective Genes Cause Disease
...Show More Authors

Variation in DNA, and genes to a lesser or greater extent, can play an important role in most diseases; that is because this variation in will reflect and affect the function of DNA, and genes (combined genes and DNA or separately). This can be affected by environment, life style, as well as the inheriting from parents and previous generations. All these factors can contribute in human diseases. There are different alterations in genes, like imbalance and inequality in chromosomes, disorder in gene (deficiency in gene, which could be complex or single disorder), and cancer. In the last decades, scientists were focus on medicine and genetics; they pay an extensive attention to reach better understanding about diseases and their cause

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
...Show More Authors

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

... Show More
View Publication
Publication Date
Fri Dec 30 2016
Journal Name
Al-kindy College Medical Journal
Deep Vein Thrombosis Predisposing Factors Analysis Using Association Rules Mining
...Show More Authors

Background: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment. Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors. Type of the study:A cross- secti

... Show More
View Publication Preview PDF