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TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by using different tools and techniques. However, this paper presents a comprehensive review of the methods and techniques used to detect brain tumor through MRI image segmentation. Lastly, the paper concludes with a concise discussion and provides a direction toward the upcoming trend of more advanced research studies on brain image segmentation and Tumor detection.

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Detection of Anti-cancer Activity of Silver Nanoparticles Synthesized using Aqueous Mushroom Extract of Pleurotus ostreatus on MCF-7 Human Breast Cancer Cell Line
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     In this research, silver nanoparticles (AgNPs) were manufactured using aqueous extract of mushroom Pleurotus ostreatus. Anticancer potential of AgNPs was investigated versus human breast cancer cell line (MCF-7). Cytotoxic response was assessed by MTT assay. AgNPs showed inhibition effect at the following concentrations 12.5, 25, 50, 100 and 200 µg/ml versus MCF-7 cell line, and all treatments had a positive result. The MCF-7 cells were inhibited up to 85.14 % at the concentration 200 μg/ml of AgNPs which reduced cells viability to 14.86%, while 12.5 μg/ml of AgNPs caused 24.23% cells inhibition with reduction of cells viability to 75.77%.

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Publication Date
Thu Nov 21 2019
Journal Name
Al-kindy College Medical Journal
Magnetic Resonance Venography Findings In A Group Of Patients With Multiple Sclerosis
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Background: Multiple sclerosis is a chronic heterogeneous demyelinating axonal and inflammatory disease involving the Central Nervous System [CNS] white matter with a possibility of gray matter involvement in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of parts of the nervous system to communicate, resulting in a wide range of signs and symptoms. Cerebral venous insufficiency theory was raised as a possible etiology for the disease at 2008 by Zamboni an Italian cardiothoracic surgeon. This theory was defeated by Multiple Sclerosis[ MS] researchers and scientists who thought that the disease is an autoimmune rather than vascular.

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Publication Date
Tue Oct 01 2019
Journal Name
The Journal Of Immunology
AhR Activation Leads to Massive Mobilization of Myeloid-Derived Suppressor Cells with Immunosuppressive Activity through Regulation of CXCR2 and MicroRNA miR-150-5p and miR-543-3p That Target Anti-Inflammatory Genes
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Abstract<p>The compound 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an environmental contaminant, is a potent ligand for aryl hydrocarbon receptor (AhR). In the current study, we made an exciting observation that naive C57BL/6 mice that were exposed i.p. to TCDD showed massive mobilization of myeloid-derived suppressor cells (MDSCs) in the peritoneal cavity. These MDSCs were highly immunosuppressive and attenuated Con A–induced hepatitis upon adoptive transfer. TCDD administration in naive mice also led to induction of several chemokines and cytokines in the peritoneal cavity and serum (CCL2, CCL3, CCL4, CCL11, CXCL1, CXCL2, CXCL5, CXCL9, G-CSF, GM-CSF, VEGF, and M-CSF) and chemokine receptors</p> ... Show More
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Publication Date
Mon Jan 01 2018
Journal Name
Biochemical Cellular Archive
Immunological and molecular detection of herpes simplex virus type 1 and 2 in patients clinically diagnosed with parkinson’s disease and multiple sclerosis
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To determine the relationship between herpes simplex virus 1, 2 and neurological disorders, sixty samples from patients with neurological diseases were collected (40 patients with Multiple sclerosis and 20 patients with Parkinson’s disease) all of whom attended both the Neurological science Hospital as well as the Neuropathology consultation Department in Baghdad Hospital In Iraq. The samples were collected in the time frame between November 2017 and April 2018. The ages of the patients that were investigated were between (17-76) years and compared to a control group consisting of 25 samples collected from apparently healthy individuals. All the studied groups were subjected to the measurement of anti-HSV 1, 2 IgG antibodies by the means

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Publication Date
Thu Jan 12 2017
Journal Name
Journal Of Agricultural And Food Chemistry
Using Standing Gold Nanorod Arrays as Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Detection of Carbaryl Residues in Fruit Juice and Milk
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Publication Date
Mon Jan 01 2024
Journal Name
Jordanian Journal Of Computers And Information Technology
BEYOND WORDS: HARNESSING SPEECH SOUND FOR SPEAKER AGE AND GENDER DETECTION USING 1D CNN ARCHITECTURE WITH SELF-ATTENTION MECHANISM
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Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Joubert Syndrome: Imaging Findings and Report of a Case
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Background: Joubert syndrome (JS) is a very rare autosomal recessive disorder characterized by agenesis of cerebellar vermis, abnormal eye movements, respiratory irregularities, and delayed generalized motor development. Retinal dystrophy and cystic kidneys may also be associated with this clinical syndrome. The importance of recognizing JS is related to the outcome and its potential complications. This syndrome is difficult to diagnose clinically because of its variable phenotype. Its neuroimaging hallmarks include the characteristic molar tooth sign and bat wing-shaped fourth ventricle

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering
Numerical analysis of a concrete foundation under a combination of a dynamic and a seismic load
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Improving in assembling technology has provided machines of higher evaluation with better resistances and managed behavior. This machinery led to remarkably higher dynamic forces and therefore higher stresses. In this paper, a dynamic investigation of rectangular machine diesel and gas engines foundation at the top surface of one-layer dry sand with various states (i.e., loose, medium and dense) was carried out. The dynamic investigation is performed numerically by utilizing limited component programming, PLAXIS 3D. The soil is accepted as flexible totally plastic material submits to Mohr-Coulomb yield basis. A harmonic load is applied at the foundation with amplitude of 10 kPa at a frequency of (10, 15 and 20) HZ and se

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Sun Jan 01 2017
Journal Name
Analytical Methods
Determination of pharmaceuticals in freshwater sediments using ultrasonic-assisted extraction with SPE clean-up and HPLC-DAD or LC-ESI-MS/MS detection
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A robust and sensitive analytical method is presented for the extraction and determination of six pharmaceuticals in freshwater sediments.

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