Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform well in certain medical image applications.The aim of this paper is to change the medical image into something that is more meaningful and easier to analyze and recognize features that helps the doctors to diagnoses the diseases .This paper views selected medical image and segmentation method that have been proposed, which are suitable for processing medical images by use the modification of the traditional interactive threshold technique. This method gave good results,and these results are testedaccordingto the measure of quality (PSNR).
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola
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The effect of air injection device on the performance of airlift pump used for water pumping has been studied numerically and experimentally. An airlift pump of dimensions 42mm diameter and 2200 mm length with conventional and modified air injection device was considered. A modification on conventional injection device (normal air-jacket type) was carried out by changing injection angle from 90 (for conventional) to 22.5 (for modified). Continuity and Navier-Stokes equations in turbulent regime with an appropriate two-phase flow model (VOF) and turbulent model ( ) in two dimensions axisymmetry flow were formulated and solved by using the known package FLUENT version (14.5). The numerical and experimental investiga
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Among all the common mechanical transmission elements, gears still playing the most dominant role especially in the heavy duty works offering extraordinary performance under extreme conditions and that the cause behind the extensive researches concentrating on the enhancement of its durability to do its job as well as possible. Contact stress distribution within the teeth domain is considered as one of the most effective parameters characterizing gear life, performance, efficiency, and application so that it has been well sought for formal gear profiles and paid a lot of attention for moderate tooth shapes. The aim of this work is to investigate the effect of pressure angle, speed ratio, and correction factor on the maxi
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Epoxy (EP) – Silica (SiO2) composites are well known composites used in microelectronic industry . So it is important to study their dielectric behavior under different conditions such as
the presence carbon black (UV absorber) and immersion in the water for 30 days .
Dielectric properties were calculated over the frequency range 102 – 106 Hz for epoxy composites with different weight % of micrometer 1.5μm SiO2 particles (60%, 65% and 70wt%) modified with 0.5wt% silane coupling agent to improve adhesion between EP and SiO2 phases .
The new novel polymers nanocomposites based modified chitosan (CS) blending with polyvinyl alcohol (PVA) and coated gold or silver nanoparticles (AuNPs), AgNPs) were synthesized from many sequence reactions as presented in (Scheme1, 2 and 3). By utilizing 1H-NMR spectroscopy, FTIR, and Field Emission Scanning electron microscope , the synthesized compounds have been identified. Molecular docking is studied, where operations are used to predict the binding status of compounds with the enzyme and to calculate the free energy (ΔG) of the compounds prepared. Also, the antibacterial activity regarding the synthesized compounds against two resistant pathogenic bacteria (G+) S. aureus and E. coli (G-) was examined in vitro compare with standard a
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