Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel,
"Automatic localization and boundary detection of retina in images using basic image processing filters",
Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013.
Abstractn/a
Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel,
"Automatic localization and boundary detection of retina in images using basic image processing filters",
Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013.
Abstractn/a
Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel,
"Automatic localization and boundary detection of retina in images using basic image processing filters",
Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013.
Abstractn/a
Hassanien, A. E., N. El-Bendary, M. Kudělka, and Václav Snášel,
"Breast cancer detection and classification using support vector machines and pulse coupled neural network",
Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 269–279, 2013.
Abstractn/a
Hassanien, A. E., N. El-Bendary, M. Kudělka, and Václav Snášel,
"Breast cancer detection and classification using support vector machines and pulse coupled neural network",
Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 269–279, 2013.
Abstractn/a
Hassanien, A. E., N. El-Bendary, M. Kudělka, and Václav Snášel,
"Breast cancer detection and classification using support vector machines and pulse coupled neural network",
Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 269–279, 2013.
Abstractn/a
TarasKotyk, N. D., A. S. Ashour, A. D. C. Victoria, T. Gaber, A. E. Hassanien, and V. Snasel,
"Detection of Dead stained microscopic cells based on Color Intensity and Contrast",
The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), 2015, , Beni Suef, Egypt, November 28-30, , 2015.
AbstractApoptosis is an imperative constituent of various processes including proper progression and functioning of the immune system, embryonic development as well as chemical-induced cell death. Improper apoptosis is a reason in numerous human/animal’s conditions involving ischemic damage, neurodegenerative diseases, autoimmune disorders and various types of cancer. An outstanding feature of neurodegenerative diseases is the loss of specific neuronal populations. Thus, the detection of the dead cells is a necessity. This paper proposes a novel algorithm to achieve the dead cells detection based on color intensity and contrast changes and aims for fully automatic apoptosis detection based on image analysis method. A stained cultures images using Caspase stain of albino rats hippocampus specimens using light microscope (total 21 images) were used to evaluate the system performance. The results proved that the proposed system is efficient as it achieved high accuracy (98.89 ± 0.76 %) and specificity (99.36 ± 0.63 %) and good mean sensitivity level of (72.34 ± 19.85 %).
Heba, T., E. - B. Nashwa, H. AboulElla, B. Yehia, and S. Vaclav,
"Retinal Feature-Based Registration Schema",
Informatics Engineering and Information Science Communications in Computer and Information Science Volume 252, 2011, pp 26-36 , Ostrava, Czech Republic, 7-9 July, 2011.
AbstractThis paper presents a feature-based retinal image registration schema. A structural feature, namely, bifurcation structure, has been used for the proposed feature-based registration schema. The bifurcation structure is composed of a master bifurcation point and its three connected neighbors. The characteristic vector of each bifurcation structure consists of the normalized branching angle and length, which is invariant against translation, rotation, scaling, and even modest distortion. The proposed schema is composed of five fundamental phases, namely, input retinal images pre-processing, vascular network detection, noise removal, bifurcation points detection in vascular networks, and bifurcation points matching in pairs of retinal images. The effectiveness of the proposed schema is demonstrated by the experiments with 12 pairs retinal images collected from clinical patients. The registration is carried out through optimizing a certain similarity function, namely, normalized correlation of images. It has been observed that the proposed schema has achieved good performance accuracy.