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
Fibro-adenoma is the most common lesion of the breast, it occurs in25%of asymptomatic women (1,2 )
It is usually a disease of early reproductive life, the peak incidence is between the ages15 and 35 years.(3,4) It presents as firm highly mobile, non tender mass .(5)
Less than 5% of fibro-adenomas grow rapidly and display the clinical and histologic characteristics of giant fibro-adenoma which is defined as a-tumour either having a diameter greater than 5 cm. And /or amass weighing more than 500 grams, and are conventionally a benign tumor of breast.(6)
Giant fibro-adenomas appear as well-circumscribed but not encapsulated masses on mammography and solid and the texture is homogenous and hypoechoic with low level echoes on U/S. (
Core decompression is one of the commonest used techniques in the handling of osteonecrosis of the pre-collapsed head of the femur. Core decompression had succeeded in preserving the hip joint and delaying the requisite for total hip replacement, but it had failed in the induction of osteogenesis in the necrotic area, thus augmenting core decompression with biological agents to induce osteogenic activity. To assess the effects of platelet-rich plasma in non-traumatic avascular necrosis of the hip joint (early stage) after core decompression. Interventional comparative study for twenty-four patients (32 hip joints) with AVN of the head of the femur was involved in this prospective study, and they were separated into two groups of 16
... Show MoreMass transfer was examined at a stationary rectangular copper electrode (cathode) by using the reduction of cupric ions as the electrochemical reaction. The influence of electrolyte temperature (25, 45, and 65 oC), and cupric ions concentration (4, 8, and 12 mM) on mass transfer coefficient were investigated by using limiting current technique. The mass transfer coefficient and hence the Sherwood number was correlated as Sh =
The data communication has been growing in present day. Therefore, the data encryption became very essential in secured data transmission and storage and protecting data contents from intruder and unauthorized persons. In this paper, a fast technique for text encryption depending on genetic algorithm is presented. The encryption approach is achieved by the genetic operators Crossover and mutation. The encryption proposal technique based on dividing the plain text characters into pairs, and applying the crossover operation between them, followed by the mutation operation to get the encrypted text. The experimental results show that the proposal provides an important improvement in encryption rate with comparatively high-speed Process
... Show MoreThe city of Derna has distinctive architectural and architectural features, like other Arab and Islamic cities in the Arab West and North Africa. Its markets and shops have taken many different forms and structural forms within the urban fabric of the central commercial zone. The meeting between the various commercial and handicraft jobs and consumers within a spatial area starting with the old markets of the dark market and the agency of the harvest and vegetable market and the mosque of the old and the square of the mosque and the Red Square and the square Kharazin. It then grew linearly towards commercial hubs that were associated with the city's expansion axes. Old markets represent the architectural and planning heritage associated
... Show MoreEat this research study features Technical Ceramics Islamic and Chinese The study of four chapters , such as the first chapter the general framework for research and containing the problem that put the following question: Mamdy effect features art on porcelain Islamic and Chinese ) , and whether there are dimensions of the aesthetic , intellectual and ideological in porcelain Islamic and Chinese with lies the importance of research in the promise of a qualitative study and add a scientific theme features art in porcelain Islamic and China , and the objectives of this study One was in the detection of features technical Ceramics Islamic and Chinese study examined the length of time the ninth century AD , and the tenth century AD , and in
... Show MoreDiabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
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