Adel Said Elmaghraby

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We propose a technique for the automated detection of malignant masses in screening mammography. The technique is based on the presence of concentric layers surrounding a focal area with suspicious morphological characteristics and low relative incidence in the breast region. Mammographic locations with high concentration of concentric layers with(More)
We provide a biasing expansion swarm approach (BESA) for using multiple simple mobile agents, with limited sensing and communication capabilities, to collaboratively search and locate an indeterminate number of emission sources in an unknown large-scale area. The key concept in this approach is swarm behavior. By applying the three properties of the swarm(More)
Previously we presented a morphologic concentric layered (MCL) algorithm for the detection of masses in screening mammograms. The algorithm achieved high sensitivity (92%) but it also generated 3.26 false positives (FPs) per image. In the present study we propose a false positive reduction strategy based on using an artificial neural network that merges(More)
In this paper, we describe a swarm-based fuzzy logic control (FLC) mobile sensor network approach for collaboratively locating the hazardous contaminants in an unknown large-scale area. The mobile sensor network is composed of a collection of distributed nodes (robots), each of which has limited sensing, intelligence and communication capabilities. An(More)
Computer assisted detection systems (CAD) in mammography incorporate two critical stages: (i) prescreening to localize suspicious regions and (ii) detailed analysis of the regions for false positive reduction. In this work, we present a new technique for automatic detection of suspicious masses for prescreening mammograms. The hypothesis of the proposed(More)
Information theoretic similarity metrics, including mutual information, have been widely and successfully employed in multimodal biomedical image registration. These metrics are generally based on the Shannon-Boltzmann-Gibbs definition of entropy. However, other entropy definitions exist, including generalized entropies, which are parameterized by a real(More)
In the real world, we have to frequently deal with searching for and tracking an optimal solution in a dynamic environment. This demands that the algorithm not only find the optimal solution but also track the trajectory of the solution in a dynamic environment. Particle swarm optimization (PSO) is a population-based stochastic optimization technique, which(More)
In this paper, we introduce a novel hierarchical approach for multiphase image segmentation. The approach presents a unified framework that unifies two basic segmentation approaches; level set methods and graph cut algorithms. In the work of El-Zehiry et al. (2007), we have presented a bimodal image segmentation approach that have the advantages of the(More)
This paper presents a novel graph cut based segmentation approach with shape priors. The model incorporates statistical shape prior information with the active contour without edges model [6]. Our model also relaxes the homogeneity constraint that assumes that the image is modeled by a piecewise constant approximation. The major contribution of this paper(More)