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
Three-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and construc
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Background : It has been suggested that pretreatment with a statin agent prior to
myocardial infarction limits myocardial
creatine kinase release, and thus may act to
limit myocardial infarct size in humans.
Objective : To examine the effect of very
early statin initiation for acute myocardial
infarction (AMI), to the extent of
myonecrosis as manifested by peak serum
creatine kinase levels.
Methods : Patients with AMI admitted to AlKindy teaching hospital cardiac care unit
from 1st February 2007 to 28th February
2008, who fulfilled the inclusion criteria
cited in the present study, were randomly
assigned into two study groups. The statin
group patients have received a single oral
dose of 40 mg
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 w
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first
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Many studied were conducted to evaluate the antihepatotoxic and antioxidant activities of Silybum marianum and proved these actions. The Naturally grown seed in Iraqi-Kurdistan Region also were studied for its chemical contents and biological activities. Vegetable oils occur in various plant parts mainly concentrated in the seeds.
In this study comparison was made between the fatty acid patterns of two plant seeds, Silybum marianum and Nigella sativa. Seed sample of Silybum marianum and Nigella sativa were exposed for extraction and isolation of the fatty acid contents using two different solvents (petroleum ether and n-hexane) at 60-80oC using soxhlet apparatus and the oily extract
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A precise evaluation of caries excavation endpoint is essential in clinical and laboratory investigations. Caries invasion differentiates dentin into structurally altered layers. This study assessed these changes using Raman spectroscopy and Vickers microhardness. Ten permanent molars with occlusal and proximal carious lesions were assessed and compared at 130 points utilizing four Raman spectroscopic peaks: phosphate v1 at 960 cm−1, amide I (1650 cm−1), amide III (1235 cm−1) and the C-H bond of the pyrrolidine ring (1450 cm−1). The phosphate-to-amide I peak ratio and collagen integrity peak ratio (amide III: C-H bond) of carious zones were calculated and compared in both lesions. The former ratio was correlated to 130 Vicke
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The advent of UNHCR reports has given rise to the uniqueness of its distinctive way of image representation and using semiotic features. So, there are a lot of researches that have investigated UNHCR reports, but no research has examined images in UNHCR reports of displaced Iraqis from a multimodal discourse perspective. The present study suggests that the images are, like language, rich in many potential meanings and are governed by clearly visual grammar structures that can be employed to decode these multiple meanings. Seven images are examined in terms of their representational, interactional and compositional aspects. Depending on the results, this study concludes that the findings support the visual grammar theory and highlight the va
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