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Azar, A. T., H. I. Elshazly, A. E. Hassanien, and A. M. Elkorany, "Random Forest Classifier for Lymph Diseases", Computer Methods and Programs in Biomedicine , Elsevier 2013 , vol. 113, issue 2, pp. 465-473 , 2014. Website
Azar, A. T., H. I. Elshazly, A. E. Hassanien, and A. M. Elkorany, "A random forest classifier for lymph diseases", Computer methods and programs in biomedicine, vol. 113, no. 2: Elsevier, pp. 465–473, 2014. Abstract
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Esraa Elhariri, N. El-Bendary, A. E. Hassanien, A. Badr, Ahmed M. M. Hussein, and V. Snasel, "Random forests based classification for crops ripeness stage", The 5th International Conference on Innovations in Bio-Inspired Computing and Applications (Springer) IBICA2014, Ostrava, Czech Republic., 22-24 June, 2014. ibica2014p25.pdf
Esraa Elhariri, N. El-Bendary, A. E. Hassanien, A. Badr, A. M. M. Hussein, and Václav Snášel, "Random forests based classification for crops ripeness stages", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 205–215, 2014. Abstract
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Hore, S., T. Bhattacharya, N. Dey, A. E. Hassanien, A. Banerjee, and S. R. B. Chaudhuri, "A Real Time Dactylology Based Feature Extractrion for Selective Image Encryption and Artificial Neural Network", Image Feature Detectors and Descriptors: Springer International Publishing, pp. 203–226, 2016. Abstract
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Mahmood, M. A., E. T. Al-Shammari, N. El-Bendary, A. E. Hassanien, and H. A. Hefny, "Recommender system for ground-level Ozone predictions in Kuwait", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 107–110, 2013. Abstract
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Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Reducing the influence of normalization on data classification", Computer Information Systems and Industrial Management Applications (CISIM), 2010 International Conference on: IEEE, pp. 609–613, 2010. Abstract
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Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Reducing the influence of normalization on data classification", Computer Information Systems and Industrial Management Applications (CISIM), 2010 International Conference on: IEEE, pp. 609–613, 2010. Abstract
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Mostafa, A., M. A. Fattah, A. Fouad, A. E. Hassanien, and T. - H. Kim, "Region growing segmentation with iterative K-means for CT liver images", Advanced Information Technology and Sensor Application (AITS), 2015 4th International Conference on: IEEE, pp. 88–91, 2015. Abstract
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Reham Gharbia, Ali Hassan El Baz, A. E. H. V. S.:, "Region-based Image Fusion Approach of Panchromatic and Multi-spectral Images", , Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2015, pp. 535-545, , Ostrava, Czech Republic, June 29 - July 1, 2015. Abstract

In this paper, a region-based image fusion approach were proposed based on the stationary wavelet transform (SWT) in conjunction with marker-controlled watershed segmentation technique. The SWT is redundant, linear and shift invariant and these properties allow SWT to be realized exploiting a recursive algorithm and gives a better approximation than the DWT. The performance of the fusion approach is illustrated via experimental results obtained with a broad series of images and the experimental results used the MODIS multi-spectral bands and Spot panchromatic band to validate the proposed image fusion technique. Moreover, the visual presentation and different evaluation criteria including the standard deviation, the entropy information, the correlation coefficient, the root mean square error, the peak signal to noise ratio and the structural similarity index was used to evaluate the obtained results. The proposed approach achieves superior results compared with the existing work.

Reham Gharbia, Ali Hassan El Baz, A. E. Hassanien, and V. Snasel, "Region-based Image Fusion Approach of Panchromatic and Multi-spectral Images", Intelligent Data Analysis and Applications: Springer International Publishing, pp. 535–545, 2015. Abstract
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Mohamed Tahoun, A. E. Hassanien, and R. Reulke, "Registration of Optical and Radar Satellite Images Using Local Features and Non-rigid Geometric Transformations", Surface Models for Geosciences: Springer International Publishing, pp. 249–261, 2015. Abstract
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Hussein, H. K., A. - E. Hassanien, and M. Nakajima, "Regular Section-PAPERS-Image Processing, Computer Graphics and Pattern Recognition-Escape-Time Modified Algorithm for Generating Fractal Images Based on Petri Net Reachability", IEICE Transactions on Information and Systems, vol. 82, no. 7: Tokyo, Japan: Institute of Electronics, Information and Communication Engineers, c1992-, pp. 1101–1108, 1999. Abstract
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Hassanien, A. - E., and M. Nakajima, "Regular Section-PAPERS-Image Processing, Computer Graphics and Pattern Recognition-Feature-Specification Algorithm Based on Snake Model for Facial Image Morphing", IEICE Transactions on Information and Systems, vol. 82, no. 2: Tokyo, Japan: Institute of Electronics, Information and Communication Engineers, c1992-, pp. 439–446, 1999. Abstract
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Sahba, F., H. R. Tizhoosh, and M. M. A. Salama, "Reinforced Medical Image Segmentation", Computational Intelligence in Medical Imaging: Techniques and Applications: Chapman and Hall/CRC, pp. 327–345, 2009. Abstract
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Reham Gharbia, Ali Hassan El Baz, A. E. Hassanien, and M. F.Tolba, Remote sensing image fusion approach based on Brovey and wavelets transforms, , 2014. Abstractibica2014_p37.pdf

This paper proposes a remote sensing image fusion approach
based on a modi ed version of Brovey transform and wavelets. The aim is
to reduce the spectral distortion in the Brovey transform and spatial dis-
tortion in the wavelets transform. The remote sensing data sets has been
chosen for the image fusion process and the data sets were selected from
di erent satellite images in south western Sinai, Egypt. Experiments were
conducted on a variety of images, and the results of the proposed image
fusion approach were compared with principle component analysis and
the traditional Brovey approach. The obtained results show that the
proposed approach achieves less de
ection and reduces the distortion.
Several quality evaluation metrics were used for the proposed image fu-
sion like standard deviation, correlation coecient, entropy information,
peak signal to noise ratio, root mean square error and structural simi-
larity index. Experimental results obtained from proposed image fusion
approach prove that the use of the Brovey with wavelets can eciently
preserve the spectral information while improving the spatial resolution
of the remote sensing.

Reham Gharbia, Ali Hassan El Baz, A. E. Hassanien, and M. F. Tolba, "Remote sensing image fusion approach based on Brovey and wavelets transforms", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 311–321, 2014. Abstract
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Reham Gharbia, Sara Ahmed, and A. E. Hassanien, "Remote Sensing Image Registration Based On Particle Swarm Optimization and Mutual Information", The Second International Conference on INformation systems Design and Intelligent Applications ((INDIA 15), Kalyani, India, January 8-9 , 2015.
Reham Gharbia, S. A. Ahmed, and A. E. Hassanien, "Remote Sensing Image Registration Based on Particle Swarm Optimization and Mutual Information", Information Systems Design and Intelligent Applications: Springer India, pp. 399–408, 2015. Abstract
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Gaber, T., A. E. Hassanien, and M. F. Tolba, "Repeated reselling permission multi-reselling approach for a license in DRM environment", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 197–202, 2013. Abstract
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Hassanien, A. E., Eid Emary, and H. M. Zawbaa, "Retinal blood vessel localization approach based on bee colony swarm optimization, fuzzy c-means and pattern search", Journal of Visual Communication and Image Representation, vol. 31: Academic Press, pp. 186–196, 2015. Abstract
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Hassaniena, A. E., E. Emarya, and H. M. Zawbaa, "Retinal blood vessel localization approach based on bee colony swarm optimization, fuzzy c-means and pattern search.", J. Visual Communication and Image Representation , vol. 31, pp. 186-196 , 2015. AbstractWebsite

Accurate segmentation of retinal blood vessels is an important task in computer aided diagnosis and surgery planning of retinopathy. Despite the high resolution of photographs in fundus photography, the contrast between the blood vessels and retinal background tends to be poor. Furthermore, pathological changes of the retinal vessel tree can be observed in a variety of diseases such as diabetes and glaucoma. Vessels with small diameters are much liable to effects of diseases and imaging problems. In this paper, an automated retinal blood vessels segmentation approach based on two levels optimization principles is proposed. The proposed approach makes use of the artificial bee colony optimization in conjunction with fuzzy cluster compactness fitness function with partial belongness in the first level to find coarse vessels. The dependency on the vessel reflectance is problematic as the confusion with background and vessel distortions especially for thin vessels, so we made use of a second level of optimization. In the second level of optimization, pattern search is further used to enhance the segmentation results using shape description as a complementary feature. Thinness ratio is used as a fitness function for the pattern search optimization. The pattern search is a powerful tool for local search while artificial bee colony is a global search with high convergence speed. The proposed retinal blood vessels segmentation approach is tested on two publicly available databases DRIVE and STARE of retinal images. The results demonstrate that the performance of the proposed approach is comparable with state of the art techniques in terms of sensitivity, specificity and accuracy.

Hassan, G., N. El-Bendary, A. E. Hassanien, S. A. M. Ali Fahmy, and V. Snasel, "Retinal Blood Vessel Segmentation Approach Based on Mathematical Morphology", International Conference on Communications, management, and Information technology (ICCMIT'2015), 2015. Abstract

Diabetic retinopathy is a disease, which forms a severe threat on sight. It may reach to blindness among working age people. By analyzing and detecting of vasculature structures in retinal images, we can early detect the diabetes in advanced stages by comparison of its states of retinal blood vessels. In this paper, we present blood vessel segmentation approach, which can be used in computer based retinal image analysis to extract the retinal image vessels. Mathematical morphology and K-means clustering are used to segment the vessels. To enhance the blood vessels and suppress the background information, we perform smoothing operation on the retinal image using mathematical morphology. Then the enhanced image is segmented using K-means clustering algorithm. The proposed approach is tested on the DRIVE dataset and is compared with alternative approaches. Experimental results obtained by the proposed approach showed that it is effective as it achieved average accuracy of 95.10% and best accuracy of 96.25%.

Hassan, G., N. El-Bendary, A. E. Hassanien, A. Fahmy, V. Snasel, and others, "Retinal blood vessel segmentation approach based on mathematical morphology", Procedia Computer Science, vol. 65: Elsevier, pp. 612–622, 2015. Abstract
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