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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 99.4048% for training and 95.8333% for testing.

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Publication Date
Wed Feb 14 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
Segmentation moon images using different segmentation methods and isolate the lunar craters
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Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and geology

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
A Review Study on Forgery and Tamper Detection Techniques in Digital Images
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Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

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Publication Date
Tue Sep 01 2020
Journal Name
Microprocessors And Microsystems
Design considerations for a microprocessor-based Doppler radar
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Publication Date
Sat Dec 30 2017
Journal Name
International Journal Of Science And Research (ijsr)
Color-based for tree yield fruits image counting
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Identifying the total number of fruits on trees has long been of interest in agricultural crop estimation work. Yield prediction of fruits in practical environment is one of the hard and significant tasks to obtain better results in crop management system to achieve more productivity with regard to moderate cost. Utilized color vision in machine vision system to identify citrus fruits, and estimated yield information of the citrus grove in-real time. Fruit recognition algorithms based on color features to estimate the number of fruit. In the current research work, some low complexity and efficient image analysis approach was proposed to count yield fruits image in the natural scene. Semi automatic segmentation and yield calculation of fruit

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Publication Date
Wed Jun 24 2020
Journal Name
Neuroimaging - Neurobiology, Multimodal And Network Applications
Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease
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Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

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Publication Date
Wed Jan 01 2020
Journal Name
University Of Plymouth
Intrinsic Control Strategies for Herpesvirus-based Vaccine Vectors
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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Anal Fissure: Is it becoming a medical disorder? Review Article
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An anal fissure which does not heal with conservative measures as sits baths and laxatives is a chronic anal fissure. Physiologically, it is the high resting tone of the internal anal sphincter that chiefly interferes with the healing process of these fissures. Until now, the gold standard treatment modality is surgery, either digital anal dilatation or lateral sphincterotomy. However, concerns have been raised about the incidence of faecal incontinence after surgery. Therefore, pharmacological means to treat chronic anal fissures have been explored. A Medline and pub med database search from 1986-2012 was conducted to perform a literature search for articles relating to the non-surgical treatment of chronic anal fissure. Pharmacological

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Publication Date
Thu May 05 2022
Journal Name
5g Impact On Biomedical Engineering
Wireless Techniques and Applications of the Internet of Medical Things
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Publication Date
Thu Aug 15 2024
Journal Name
Journal Of Ethnicity In Substance Abuse
Knowledge, attitude, and frequency of hookah smoking among medical students
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Publication Date
Mon Oct 27 2025
Journal Name
The Clinical Teacher
When Patients Say No: Rethinking Refusal in Bedside Medical Education
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ABSTRACT<sec> <title>Background

Bedside clinical teaching is a fundamental part of the medical education that offers invaluable opportunities for the students to build and improve their clinical and communication skills. However, there is a growing concern about the increasing refusal of patients to participate in clinical sessions, especially in certain settings where there are sensitive cultural traditions and decreased trust in institutions.

Aim

This paper discusses patient refusal duri

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