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
The incorporation of safety characteristics into the traditional pavement structural design or in the functional evaluation of pavement condition has not been established yet. The design has focused on the structural capacity of the roadway so that the pavement can withstand specific level of repetitive loading over the design life. On the other hand, the surface texture condition was neither included in the AASHTO design procedure nor in the present serviceability index measurements.
The pavement surface course should provide adequate levels of friction and ride quality and maintain low levels of noise and roughness. Many transportation departments perform routine skid resistant testing, the type of equipment us
... Show MoreThis study includes the application of non-parametric methods in estimating the conditional survival function of the Beran method using both the Nadaraya-Waston and the Priestley-chao weights and using data for Interval censored and Right censored of breast cancer and two types of treatment, Chemotherapy and radiation therapy Considering age is continuous variable, through using (MATLAB) use of the (MSE) To compare weights The results showed a superior weight (Nadaraya-Waston) in estimating the survival function and condition of Both for chemotherapy and radiation therapy.
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Abstract
Pneumatic processes sequence (PPS) is used widely in industrial applications. It is common to do a predetermined PPS to achieve a specific larger task within the industrial application like the PPS achieved by the pick and place industrial robot arm. This sequence may require change depending on changing the required task and usually this requires the programmer intervention to change the sequence’ sprogram, which is costly and may take long time. In this research a PLC-based PPS control system is designed and implemented, in which the PPS is programmed by demonstration. The PPS could be changed by demonstrating the new required sequence via the user by following simple series of manual steps without h
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Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras
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Olfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od
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Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal
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The study showed that all extracts (aqueous, ethanolic and acetonic) of the leaves of Eucalyptus and Myrtus plants had a inhibitory effect on the growth of all types of yeasts studied, acetone extract recorded the highest inhibition of yeastat 100ppm concentration,The inhibition was 35mm, 34mm, 24mm and 20mm for Candida parapsilosis, Candida glabrata, Candida tropicalis and Candida albicans respectively, The experiments above showed the least significant differences at 0.05 level.The results ofE. Cammldulensis ethanolic tincture analysis has shown the presence of 44 biologically active substances. The main Eucalyptus leaves component was: 2-Bicyclo (2-2.1) heptanol (12.37%), Ledol (8.23%),1,2,4- Benzenetriol (8.45%) and that contain spathul
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