Publications

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Book
Hassanien, A. E., M. M. Fouad, A. A. Manaf, M. Zamani, R. Ahmad, and J. Kacprzyk, Multimedia Forensics and Security: Foundations, Innovations, and Applications, , Germany , Springer, 2017. AbstractWebsite

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Book Chapter
Mostafa, A., A. E. Hassanien, and H. A. Hefny, " Grey Wolf Optimization-Based Segmentation Approach for Abdomen CT Liver Images", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI, 2017. Abstract

In the recent days, a great deal of researches is interested in segmentation of different organs in medical images. Segmentation of liver is as an initial phase in liver diagnosis, it is also a challenging task due to its similarity with other organs intensity values. This paper aims to propose a grey wolf optimization based approach for segmenting liver from the abdomen CT images. The proposed approach combines three parts to achieve this goal. It combines the usage of grey wolf optimization, statistical image of liver, simple region growing and Mean shift clustering technique. The initial cleaned image is passed to Grey Wolf (GW) optimization technique. It calculated the centroids of a predefined number of clusters. According to each pixel intensity value in the image, the pixel is labeled by the number of the nearest cluster. A binary statistical image of liver is used to extract the potential area that liver might exist in. It is multiplied by the clustered image to get an initial segmented liver. Then region growing (RG) is used to enhance the segmented liver. Finally, mean shift clustering technique is applied to extract the regions of interest in the segmented liver. A set of 38 images, taken in pre-contrast phase, was used for liver segmentation and testing the proposed approach. For evaluation, similarity index measure is used to validate the success of the proposed approach. The experimental results of the proposed approach showed that the overall accuracy offered by the proposed approach, results in 94.08% accuracy.

Mouhamed, M. R., A. Darwish, and A. E. Hassanien, "2D and 3D Intelligent Watermarking", Handbook of Research on Machine Learning Innovations and Trends: IGI Global, pp. 652–669, 2017. Abstract
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Mostafa, A., A. Fouad, M. A. Fattah, A. E. Hassanien, and H. Hefny, "Artificial Bee Colony Based Segmentation for CT Liver Images", Medical Imaging in Clinical Applications: Springer International Publishing, pp. 409–430, 2016. Abstract
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Mouhamed, M. R., H. M. Zawbaa, E. T. Al-Shammari, A. E. Hassanien, and V. Snasel, "Blind watermark approach for map authentication using support vector machine", Advances in security of information and communication networks: Springer Berlin Heidelberg, pp. 84–97, 2013. Abstract
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Mahmood, M. A., N. El-Bendary, A. E. Hassanien, and H. A. Hefny, "Classification Approach Based on Rough Mereology", Recent Advances in Intelligent Informatics: Springer International Publishing, pp. 175–184, 2014. Abstract
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Alnashar, H. S., M. A. Fattah, M. M. Mosbah, and A. E. Hassanien, "Cloud computing framework for solving virtual college educations: A case of egyptian virtual university", Information Systems Design and Intelligent Applications: Springer India, pp. 395–407, 2015. Abstract
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Mohamed Tahoun, Abd El Rahman Shabayek, R. Reulke, and A. E. Hassanien, "Co-registration of Satellite Images Based on Invariant Local Features", Intelligent Systems' 2014: Springer International Publishing, pp. 653–660, 2015. Abstract
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Hassanien, A. - E., M. G. Milanova, T. G. Smolinski, and A. Abraham, "Computational intelligence in solving bioinformatics problems: Reviews, perspectives, and challenges", Computational Intelligence in Biomedicine and Bioinformatics: Springer Berlin Heidelberg, pp. 3–47, 2008. Abstract
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Hassanien, A. - E., M. G. Milanova, T. G. Smolinski, and A. Abraham, "Computational intelligence in solving bioinformatics problems: Reviews, perspectives, and challenges", Computational Intelligence in Biomedicine and Bioinformatics: Springer Berlin Heidelberg, pp. 3–47, 2008. Abstract
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Terzopoulos, D., C. McIntosh, T. McInerney, and G. Hamarneh, "Deformable Organisms", Computational Intelligence in Medical Imaging: Techniques and Applications: Chapman and Hall/CRC, pp. 433–474, 2009. Abstract
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El-Bendary, N., V. Snasel, G. Adam, F. Mansour, N. I. Ghali, O. S. Soliman, and A. E. Hassanien, "E-Contract Securing System Using Digital Signature Approach", Advanced Communication and Networking: Springer Berlin Heidelberg, pp. 183–189, 2011. Abstract
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El-Bendary, N., V. Snasel, G. Adam, F. Mansour, N. I. Ghali, O. S. Soliman, and A. E. Hassanien, "E-Contract Securing System Using Digital Signature Approach", Advanced Communication and Networking: Springer Berlin Heidelberg, pp. 183–189, 2011. Abstract
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Ayeldeen, H., M. A. Mahmood, and A. E. Hassanien, "Effective Classification and Categorization for Categorical Sets: Distance Similarity Measures", Information Systems Design and Intelligent Applications: Springer India, pp. 359–368, 2015. Abstract
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Watchareeruetai, U., T. Matsumoto, Y. Takeuchi, H. Kudo, and N. Ohnishi, "Efficient construction of image feature extraction programs by using linear genetic programming with fitness retrieval and intermediate-result caching", Foundations of Computational Intelligence Volume 4: Springer Berlin Heidelberg, pp. 355–375, 2009. Abstract
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Watchareeruetai, U., T. Matsumoto, Y. Takeuchi, H. Kudo, and N. Ohnishi, "Efficient construction of image feature extraction programs by using linear genetic programming with fitness retrieval and intermediate-result caching", Foundations of Computational Intelligence Volume 4: Springer Berlin Heidelberg, pp. 355–375, 2009. Abstract
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Abder-Rahman Ali, Micael Couceiro, A. M. Anter, and A. E. Hassanien, "Evaluating an Evolutionary Particle Swarm Optimization for Fast Fuzzy C-Means Clustering on Liver CT Images", Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies, USA, IGI, 2014. Abstract

An Evolutionary Particle Swarm Optimization based on the Fractional Order Darwinian method for
optimizing a Fast Fuzzy C-Means algorithm is proposed. This chapter aims at enhancing the performance
of Fast Fuzzy C-Means, both in terms of the overall solution and speed. To that end, the concept
of fractional calculus is used to control the convergence rate of particles, wherein each one of them
represents a set of cluster centers. The proposed solution, denoted as FODPSO-FFCM, is applied on
liver CT images, and compared with Fast Fuzzy C-Means and PSOFFCM, using Jaccard Index and
Dice Coefficient. The computational efficiency is achieved by using the histogram of the image intensities
during the clustering process instead of the raw image data. The experimental results based on the
Analysis of Variance (ANOVA) technique and multiple pair-wise comparison show that the proposed
algorithm is fast, accurate, and less time consuming.

Mostafa, A., A. E. Hassanien, and H. A. Hefny, "Grey Wolf Optimization-Based Segmentation Approach for Abdomen CT Liver Images", Handbook of Research on Machine Learning Innovations and Trends: IGI Global, pp. 562–581, 2017. Abstract
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Mokhtar, U., M. A. S. Ali, A. E. Hassanien, and H. Hefny, "Identifying two of tomatoes leaf viruses using support vector machine", Information Systems Design and Intelligent Applications: Springer India, pp. 771–782, 2015. Abstract
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Mahmood, M. A., N. El-Bendary, Jan Platoš, A. E. Hassanien, and H. A. Hefny, "An Intelligent Multi-agent Recommender System", Innovations in Bio-inspired Computing and Applications: Springer International Publishing, pp. 201–213, 2014. Abstract
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Mahmoud, R., N. El-Bendary, H. M. O. Mokhtar, A. E. Hassanien, and H. A. Shaheen, "Machine Learning-Based Measurement System for Spinal Cord Injuries Rehabilitation Length of Stay", Intelligent Data Analysis and Applications: Springer International Publishing, pp. 523–534, 2015. Abstract
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Ali, A. F., A. Mostafa, G. I. Sayed, M. A. Fattah, and A. E. Hassanien, "Nature Inspired Optimization Algorithms for CT Liver Segmentation", Medical Imaging in Clinical Applications: Springer International Publishing, pp. 431–460, 2016. Abstract
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Abdelaziz, A., Moustafa Zein, M. Atef, A. Adl, K. K. A. Ghany, and A. E. Hassanien, "An Orphan Drug Legislation System", Intelligent Systems' 2014: Springer International Publishing, pp. 389–399, 2015. Abstract
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Abder-Rahman Ali, Micael Couceiro, A. Anter, and A. - E. Hassanien, "Particle swarm optimization based fast fuzzy C-means clustering for liver CT segmentation", Applications of Intelligent Optimization in Biology and Medicine: Springer International Publishing, pp. 233–250, 2016. Abstract
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Yakoub, F., Moustafa Zein, K. Yasser, A. Adl, and A. E. Hassanien, "Predicting personality traits and social context based on mining the smartphones SMS data", Intelligent Data Analysis and Applications: Springer International Publishing, pp. 511–521, 2015. Abstract
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