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A New Method for Detecting Cerebral Tissues Abnormality in Magnetic Resonance Images
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We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). Standard Deviation, Mean, Energy and Entropy are extorted using the histogram approach for each merger space. These features are found to be higher in occurrence in the tumor region than the non-tumor one. MRI scans of the five brains with 60 slices from each are utilized for testing the proposed method’s authenticity. These brain images (230 slices as normal and 70 abnormal) are accessed from the Internet Brain Segmentation Repository (IBSR) dataset. 60% images for training and 40% for testing phase are used. Average classification accuracy as much as 98.02% (training) and 98.19% (testing) are achieved.

Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Cognitive Effects of Tumor and Surgical Treatment in Patients with Cerebral Gliomas
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Background: Quality of life in brain tumor patients is an emerging issue and has prompted neurosurgeons to recon¬sider the need for cognitive assessment in the course of treatment. To date there has been a lack of comprehensive neuropsychological assessment performed preoperatively and in the acute postoperative period in our hospitals.Objectives: to establish the effects of tumors and their surgical treatment, from a neuropsychological perspective, on cognitive functioning in patients with cerebral Gliomas. Methods: This is a prospective study conducted in the Neurosurgical Hospital in Baghdad, Iraq, during the period from January 1999 to January 2001. Any patient admitted during the period of the study with clinical history, signs, sy

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
PHOTO DYNAMIC THERAPY (PDT) WITH BIOLOGICAL TISSUES USING ND:GLASS LASER
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A Photo Dynamic Therapy (PDT) is a technique which is used with Laser to treat many of cancer
tissues. This paper deals with the relatively new therapeutic technique (PDT) with pulsed Nd:glass Laser
which was applied to human soft tissues (Ovary and Kidney tissues), and to the hard tissues (freshly
extracted human teeth), with power density of 280 watt/mm2 and exposure time 330 usec. Different
dyes (Blue, methylene, eosin, and orange) were applied to the area before irradiation to study the effect
of the pigments on the laser interaction with biological tissues. The zone of treatment (Z-necrosis) with
aid of MATLAB was determined. The relationship of zone of treatment with exposure time,
accumulated damage and fracti

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Publication Date
Fri Jul 01 2022
Journal Name
Health Science Reports
Immunohistochemical expression of angiotensin‐converting enzyme 2 in superficial and deep maxillofacial tissues: A cross‐sectional study
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Abstract<sec><title>Background and Aims

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

Methods

The immunohistochemical expression of ACE2 was analyzed in 95 specimens from maxillofacial tissues and 10 specimens o

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
Efficient method to Recognition of Anemia Images based on Moment Invariants and Decision tree classifier
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Anemia is one of the common types of blood diseases, it lead to lack of number of RBCs (Red Blood Cell) and amount hemoglobin level in the blood is lower than normal.
In this paper a new algorithm is presented to recognize Anemia in digital images based on moment variant. The algorithm is accomplished using the following phases: preprocessing, segmentation, feature extraction and classification (using Decision Tree), the extracted features that are used for classification are Moment Invariant and Geometric Feature.
The Best obtained classification rates was 84% is obtained when using Moment Invariants features and 74 % is obtained when using Geometric Feature. Results indicate that the proposed algorithm is very effective in detect

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
A proposed method for cleaning data from outlier values using the robust rfch method in structural equation modeling
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Scopus (2)
Scopus
Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
The Digital Change Detection for Low Resolution Satellite Images in Weathering Estimation
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      The detection and estimation of weathering conditions have become a very important daily necessity in our life. For this purpose, several satellites of low resolution imagery were launched by the weathering and environmental agencies. The important weather paremeters are temperuter, wind direction,  velocity, clould and humidity, etc. The low resolution images often deal with large-scale phenomena and the interpretation and projection of the produced data requires continuous development of tools and criteria.              In this paper, the low spatial resolution data generated by the moderate resolution imaging spectroradiometer (MODIS) were used to monitor the cloud density and direction above Iraq and i

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Scopus Crossref
Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
The Effect of Magnetic Water for Chemical Fertilizer in Tomato Plant
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The research aims to find ways to minimize the use of quantities of chemical fertilizers in agriculture in order to get to an environment that is free of contaminants. Magnetized water technology used in the experience of planting seeds of tomatoes Thomson type to obtain a higher efficiency to absorb fertilizer NRK in the protected environment of the period from February to June. Magnetized water system used locally made levels Gaues (4800,2500,1500) concentrations of 50 to 100% for each level and the rate of (4) replicates, and results indicated that the severity of the magnet (4800 Gaues) and a concentration of 50% gave the highest percentage of tomato fruit size and intensity ( 1500 Gaues) and a concentration of 100% did not give any inc

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Crossref
Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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Publication Date
Wed Mar 01 2017
Journal Name
Un Published
Search Engine for Identification of Personal Images
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