Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extraction of features like mass lesions in mammograms for early detection of breast cancer. The proposed technique is based on a four-step procedure: (a) the preprocessing of the image is done, (b) regions of interest (ROI) specification, (c) supervised segmentation method includes two stages performed using the minimum distance (MD) criterion, and (d) feature extraction based on Gray level Co-occurrence matrices GLCM for the identification of mass lesions. The method suggested for the detection of mass lesions from mammogram image segmentation and analysis was tested over several images taken from Al-Ilwiya Hospital in Baghdad, Iraq. The proposed technique shows better results
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It is not often easy to identify a certain group of words as a lexical bundle, since the same set of words can be, in different situations, recognized as idiom, a collocation, a lexical phrase or a lexical bundle. That is, there are many cases where the overlap among the four types is plausible. Thus, it is important to extract the most identifiable and distinguishable characteristics with which a certain group of words, under certain conditions, can be recognized as a lexical bundle, and this is the task of this paper.
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The aim of the study is to detect the malignant conditions of the skin tumors through the features of optical images. This research included some of image processing techniques to detect skin cancer as a strong threat to human beings' lives. Using image processing and analysis methods to improves the ability of pathologists to detect this disease leading to more specified diagnosis and better treatment of them. One hundred images were collected from Benign and Malignant tumors and some appropriate image features were calculated, like Maximum Probability, Entropy, Coefficient of Variation, Homogeneity and Contrast, and using Minimum Distance method to separate these images. These features with Minimum Distance as a proposed making decision a
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Objectives: The present study aims to evaluate effectiveness of educational program the nurses' knowledge towards early prediction of acquired weakness in the intensive care unit.
Methodology: A pre-experimental study design (comparison of two groups), which was achieved through the pre and post-test method for the study sample through the application of an educational program in the intensive care unit of Al-Zahra Teaching Hospital in Kut city, Wasit Governorate. The study was conducted for the period from 28th April 2022 to 15th August 2022 by selecting a purposive (non-probability) sample for this study. The study sample size was (52) nu
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Background: Using dual-energy X-ray absorptiometry, body fat mass has been determined. The assessment of body fat mass was conducted utilizing dual-energy X-ray absorptiometry analysis of the pelvis and vertebral column. While it is acknowledged that osteoporosis can impact both body fat mass and bone mineral density, the particulars of this relationship currently remain uncertain. Objective: The aim of the present investigation is to assess gender differences in the effects of osteoporosis on the body fat mass of the upper and lower extremities. Method: 170 individuals participated (85 males and 85 females) in this study. Patients who presented with bone discomfort consisted of 40 males and 40 females. In addition, 90 apparently he
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Water level and distribution is very essential in almost all life aspects. Natural and artificial lakes represent a large percentage of these water bodies in Iraq. In this research the changes in water levels are observed by calculating the areas of five different lakes in five different regions and two different marshes in two different regions of the country, in a period of 12 years (2001 - 2012), archived remotely sensed images were used to determine surface areas around lakes and marshes in Iraq for the chosen years . Level of the lakes corresponding to satellite determined surface areas were retrieved from remotely sensed data .These data were collected to give explanations on lake level and surface area fluctuations. It is imp
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