Breast cancer is one of the most common malignant diseases among women;
Mammography is at present one of the available method for early detection of
abnormalities which is related to breast cancer. There are different lesions that are
breast cancer characteristic such as masses and calcifications which can be detected
trough this technique. This paper proposes a computer aided diagnostic system for
the extraction of features like masses and calcifications lesions in mammograms for
early detection of breast cancer. The proposed technique is based on a two-step
procedure: (a) unsupervised segmentation method includes two stages performed
using the minimum distance (MD) criterion, (b) feature extraction based on Gray
level Co-occurrence matrices GLCM for the identification of masses and
calcifications lesions. The method suggested for the detection of abnormal lesions
from mammogram image segmentation and analysis was tested over several images
taken from National Center for Early Detection of cancer in Baghdad.
Volunteerism is an element included in many human cultures. It represents a positive cooperative act between individuals and groups. It expresses the social value systems. As a social phenomenon, it develops in societies according to innumerous circumstances and conditions. This study uses a functional approach that assumes that volunteering performs six functions for volunteers. Namely, we assume that volunteering (1) creates a sense of protection (2) meets significant cultural values (3) improves professional status of volunteers, (4) strengthens their social relationships, (5) helps them achieve a better understanding of life, and finally, (6) enhances their outlook and self-esteem. The central aim of the study is to discuss these fun
... Show MoreAs a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand
... Show MoreComputer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead
... Show MoreMany recent satellite image compression methods depends on removing the spectral and spatial redundancies within image only , such these methods known as intra-frame(image) coding such as predictive and transformed based techniques , but these contributions needs a hard work in order to improve the compression performance also most of them are applied on individual data. The other trend is to exploit the temporal redundancy between the successive satellite images captured for the same area from different views, different sensors, or at different times, which will be much correlated and removing this redundancy will improve the compression performance and this principle known as inter-frame(image) coding .In this paper, a latest powerful
... Show MoreBreast cancer is the most common malignancy affecting women's health, with an increasing incidence worldwide. This study aimed to measure the intracellular concentration of the hypoxia-inducible factor 1 α (HIF-1α), tumor suppression protein p53, and estradiol (E2) in tumor tissues of adult females with breast cancer and their relation to tumor grade, tumor size, and lymph node metastases (LNM). The study was conducted on 65 adult female participants with breast mass admitted to the operating theater in Al-Hussein Teaching Hospital and Al-Habboby Teaching Hospital in Nasiriyah, Iraq, from January to November 2021. Fresh breast tumor tissues were collated and homogenized for intracellular biochemical analysis using the enzyme-linked immuno
... Show MoreCurrently voting process is paper based form, by using voting card or paper; thus the counting method is done manually, which exhausts a lot of time. Obsolete votes may be possibly occurring. This paper introduced a system in which voting and counting is done with the help of computer. The election process would be easier, it saves time, avoid errors while counting and obsolete votes are reduced. Electronic voting (E-voting) system is a voting system in which the election related data is stored and handled digitally, it would become the quickest, cheapest, and the most efficient way to administer election and count vote it is considered a means to further enhance and strengthen the democratic processes in modern information societies. Th
... Show MoreImage compression is a serious issue in computer storage and transmission, that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com
... Show MoreCurrently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload.
Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and def
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