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
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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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n
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Background: Hip fractures are common, morbid, and costly health events that threaten independence and function of older patients . Early functional recovery is extremely important for elderly patients with femoral intertrochanteric fractures to shorten their hospital stay, omit the necessity of the further nursing and care services, and reduce associated medical expenditures . Assessment of (ADL) is an important predictor of outcomes Of orthopedic surgery in very early postoperative period at two weeks and a month postoperatively using Japanese orthopedic score get a quick recovery of ADL & return the patient to his or her premorbid level function reducing the morbidity and mortality.
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Although rare, coarctation of aorta is a treatable cause of hypertension, transcatheter dilatation by balloon with or without stent are a well-known treatment strategy
ABSTRACT Background: Tuberculosis is a worldwide infectious disease in spite of advancement in health care system. Tuberculous lymphadenitis is the most prevalent form of extra pulmonary tuberculosis with predilection of cervical lymph nodes. Objectives: To evaluate the reliability of grey scale ultrasonography together with color Doppler in the diagnosis of cervical tuberculous lymph adenitis and evaluation of early therapeutic response. Subjects and methods:From July 2015 to May 2016 in Al-Karama teaching hospital /Kut city- Wasit-Iraq, 25 patients (14 males and 11 females) with ages range from (6-50) years. Ultrasonography examination was done for all patients and grey scale criteria (distribution, size, shape, echogenicity, echogenic hi
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This research was conducted in order to monitor and measure the dimensions of media policy in satellite channels directed from the point of view of the communicator, and this research is classified among the descriptive studies, as the researcher used the survey method to answer the questions that were formulated in light of the research problem represented by the main question: What are the dimensions of media policy in Directed satellite channels? .
To achieve the objectives of the study, the researcher used the following tools:
The questionnaire, in order to survey the attitudes of communicators about the extent to which the media policy during crises reflects on their professional standards. The research community is represente
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Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th
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Background: Globally, breast cancer is the second leading cause of death among women in Iraq. Several genetic and environmental factors are associated..
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This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.
Experimental results shows LPG-
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