Book Chapters (Total=23)

• [1] Eladawi, N., ElTanboly, A., Elmogy, M., Ghazal, M., Aboelfetouh, A., Riad, A., El-Azab, M., Giridharan, G., and El-Baz, A.,: Automatic Detection of Early Signs of Diabetic Retinopathy Based on Feature Fusion from OCT and OCTA Scans, Big Data in Multimodal Medical Imaging, Taylor & Francis, (In Press).

• [2] Eladawi, N., Elmogy, M., Ghazal, M., Mahmoud, H., Aboelfetouh, A., Riad, A., Keynton, R., and El-Baz, A.: Computer-Aided Diagnosis System Based on a Comprehensive Local Features Analysis for Early Diabetic Retinopathy Detection using OCTA, Computer-Assisted Diagnosis Diabetes and Fundus OCT, Elsevier, (In Press).
• [3] Eladawi, N., Elmogy, M., Ghazal, M., Alhalabi, M., T., Mahmoud, H., Mahmoud, A. H., Aboelfetouh, A., Riad, A., Keynton, R., and El-Baz, A.: Optical Coherence Tomography: A Review, Computer-Assisted Diagnosis Diabetes and Fundus OCT, Elsevier, (In Press).

• [4] Mahmoud, H., Eladawi, N., Elmogy, M., Ghazal, M., Alhalabi, M. T., Mahmoud, A. H., Aboelfetouh, A., Riad, A., Schaal, S., and El-Baz, A.: Retinal Diseases Diagnosis Based on Optical Coherence Tomography Angiography (OCTA), Computer-Assisted Diagnosis Diabetes and Fundus OCT, Elsevier, (In Press).

• [5] El-Gamal, F., Elmogy, M., Hajjdiab, H., Khalil, A., Ghazal, M., Mahmoud, A., Soliman, H., Atwan, A., Suri, J., Barnes, G., and El-Baz A.: A local/regional computer-aided system for the diagnosis of mild cognitive impairment. In Neurological Disorders and Imaging Physics, Volume 3 (Application to autism spectrum disorders and Alzheimer's), 2053-2563, pages 11–1 to 11–26. IOP Publishing, 2019.

• [6] El-Gamal, F., Elmogy, M., Khalil, A., Hajjdiab, H., Ghazal, M., Mahmoud, A., Soliman, H., Atwan, A., Barnes, G., and El-Baz, A.: Current trends and considerations of Alzheimer's disease. In Neurological Disorders and Imaging Physics, Volume 3 (Application to autism spectrum disorders and Alzheimer's), 2053-2563,  pages 13–1 to 13–107. IOP Publishing, 2019.

• [7] Abdel Maksoud, E. A., Ramadan, M., Barakat, S., and Elmogy, M.: A Computer-Aided Diagnoses System for Detecting Multiple Ocular Diseases Using Color Retinal Fundus Images, Machine Learning in Bio-Signal Analysis and Diagnostic Imaging, pp. 19-52, Elsevier Inc., 2019.

• [8] Abdel Maksoud, E. A., Barakat, S., and Elmogy, M.: Medical Images Analysis Based on Multilabel Classification, Machine Learning in Bio-Signal Analysis and Diagnostic Imaging, pp. 209-245, Elsevier Inc., 2019.

• [9] Reda, I., Shalaby, A., Elmogy, M., Aboulfotouh, A., Abou El-Ghar, M., Elmaghraby, A., and El-Baz, A.: Diagnosing Prostate Cancer Based on Deep Learning with a Stacked Non-Negativity Constraint Auto-encoder, Prostate Cancer Imaging: An Engineering and Clinical Perspective, Taylor & Francis,  (In Press).

• [10] Reda, I., McClure, P., Shalaby, A., Elmogy, M., Aboulfotouh, A., Aou El-Ghar, M., El-Melegy, M., Suri, J., and El-Baz, A.: Prostate Segmentation from DW-MRI Using Level-set Guided by Nonnegative Matrix Factorization, Prostate Cancer Imaging: An Engineering and Clinical Perspective, Taylor & Francis,  (In Press).

• [11] Adel, E., El-Sappagh, S., Barakat, S., and Elmogy, M.: Ontology-based electronic health record semantic interoperability: A survey, U-Healthcare Monitoring Systems: Design and Applications, Vol. (1), pp. 315-352, Elsevier Inc., 2019.

• [12] Adel, E., El-Sappagh, S., Barakat, S., and Elmogy, M.: A unified fuzzy ontology for distributed electronic health record semantic interoperability, U-Healthcare Monitoring Systems: Design and Applications, Vol. (1), pp. 354-395, Elsevier Inc., 2019.

• [13] Shoaip, N., El-Sappagh, S., Barakat, S., and Elmogy, M.: Reasoning methodologies in clinical decision support systems: A literature review, U-Healthcare Monitoring Systems: Design and Applications, Vol. (1), pp. 61-87, Elsevier Inc., 2019.

• [14] Shoaip, N., El-Sappagh, S., Barakat, S., and Elmogy, M.: Ontology enhanced fuzzy clinical decision support system, U-Healthcare Monitoring Systems: Design and Applications, Vol. (1), pp. 147-177, Elsevier Inc., 2019.

• [15] Abdel Maksoud, E. A., Elmogy, M., and Al-Awadi, R. M.: Segmentation of Brain Tumor from MRI Images Based on Hybrid Clustering Techniques, Handbook of Research on Machine Learning Innovations and Trends, the Advances in Computational Intelligence and Robotics (ACIR) Book Series, IGI Global, pp. 114-135, 2017.

• [16] Shoaip, N., Elmogy, M., Riad, A., Zaghloul, H., and Badria, F.: Early-Stage Ovarian Cancer Diagnosis Using Fuzzy Rough Sets with SVM Classification, Handbook of Research on Machine Learning Innovations and Trends, the Advances in Computational Intelligence and Robotics (ACIR) Book Series, IGI Global, pp. 43-60, 2017.

• [17] El-Sappagh, S., Elmogy, M., Riad, A., Zaghloul, H., and Badria, F.: A Preparation Framework for EHR Data to Construct CBR Case-Base, Handbook of Research on Machine Learning Innovations and Trends, the Advances in Computational Intelligence and Robotics (ACIR) Book Series, IGI Global, pp. 345-378, 2017.

• [18] Hamouda, K., Elmogy, M., and El-Desouky, B. S.: A Fragile Watermarking Chaotic Authentication Scheme Based on Fuzzy C-Means for Image Tamper Detection, Handbook of Research on Machine Learning Innovations and Trends, the Advances in Computational Intelligence and Robotics (ACIR) Book Series, IGI Global, pp. 856-878, 2017.

• [19] Reda, I., Elmogy, M., Aboulfotouh, A., Ismail, M., El-Baz, A., and Keynton, R.: Prostate Segmentation using Deformable Model-Based Methods, Biomedical Image Segmentation: Advances and Trends, A. El-Baz, X. Jiang, and J. Suri (Editors), Francis and Taylor, ch. 13, pp. 289--308, 2016.

• [20] Adbel Maksoud, E. A., Elmogy, M.: 3D Brain Tumor Segmentation Based on Hybrid Clustering Techniques Using Multi-views of MRI, Medical Imaging in Clinical Applications: Algorithms and Computer-Based Approaches, Studies in Computational Intelligence, Vol. 651, Springer, pp. 81-104, 2016.

• [21] Ali, H., Elmogy, M., El-Daydamony, E., Atwan, A., Soliman, H.: Magnetic Resonance Brain Imaging Segmentation Based on Cascaded Fractional-Order Darwinian Particle Swarm Optimization and Mean Shift Clustering, Medical Imaging in Clinical Applications: Algorithms and Computer-Based Approaches, Studies in Computational Intelligence, Vol. 651, Springer, pp. 55-80, 2016.

• [22] Ibraheem, M. R., Elmogy, M.: Automated Segmentation and Classification of Hepatocellular Carcinoma Using Fuzzy C-Means and SVM, Medical Imaging in Clinical Applications: Algorithms and Computer-Based Approaches, Studies in Computational Intelligence, Vol. 651, Springer, pp. 193-210, 2016.

Elmogy, M., Habel, C., and Zhang, J.: A Cognitively Motivated Route-Interface for Mobile Robot Navigation, vol. 6 of Cognitive Systems Monographs. Springer Berlin/Heidelberg, pp. 73–82, 2009.