Computer Science Lecturer

Faculty of Computers & Information Technology, Future University in Egypt

Biography:

PhD. Thesis Title: “Intelligent Machine learning Algorithms for processing the Brain Images”

Heba Mohsen is a Lecturer of Computer Science. She received her BSc in computer science from Faculty of Computer and Information Sciences, Ain Shams University in 2006. She received her MSc and PhD degrees in Computer Science specialized in developing intelligent systems for detection and identification of brain tumors from Ain Shams University, in 2012 and 2018, respectively.
Heba started teaching at Faculty of Computers and Information Technology (FCIT), Future University in Egypt (FUE) as a Full-time in Fall 2006. Over these years, she has been very active and eager to learn. She taught many courses and has been member in the responsible team for updating the curriculums in FCIT Quality assurance unit for NQAEE accreditation. She also participated in the organization of several local conferences and workshops that was held by FCIT-FUE.

Research Interests:

• Machine Learning
• Medical Image processing
• Image Segmentation/Classification
• Deep Learning Neural Networks

Publications:

• Heba Mohsen, El-Sayed A. El-Dahshan, El-Sayed M. El-Horbaty and Abdel-Badeeh M. Salem (2018). Classification using Deep Learning Neural Networks for Brain Tumors, Future Computing and Informatics Journal 3(1), pp. 68-71.
• Heba Mohsen, El-Sayed A. El-Dahshan, El-Sayed M. El-Horbaty and Abdel-Badeeh M. Salem (2017). Classification of Brain MRI for Alzheimer's Disease Based on Linear Discriminate Analysis, Egyptian Computer Science Journal 41(3), pp. 44-52
• Heba Mohsen, El-Sayed A. El-Dahshan, El-Sayed M. El-Horbaty and Abdel-Badeeh M. Salem (2017). Brain Tumor Type Classification Based on Support Vector Machine in Magnetic Resonance Images, Annals Of “Dunărea de Jos” University Of Galați, Mathematics, Physics, Theoretical Mechanics, Fascicle II, Year IX (XL) 2017, No. 1
• Heba Mohsen, El-Sayed A. El-Dahshan, El-Sayed M. El-Horbaty and Abdel-Badeeh M. Salem (2017). Intelligent Methodology for Brain Tumors Classification in Magnetic Resonance Images, International Journal of Computers 11, pp.1-5.
• Heba Mohsen, El-Sayed A. El-Dahshan, El-Sayed M. El-Horbaty and Abdel-Badeeh M. Salem (2016). A Comparative Study of Segmentation Techniques for Brain Magnetic Resonance Images, Athens: ATINER'S Conference Paper Series, No: COM2016-1994.
• El-Sayed A. El-Dahshan, Heba M. Mohsen, Kenneth Revett and Abdel-Badeeh M. Salem (2014). Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm. Expert systems with Applications 41(11), pp.5526-5545. Link
• Heba Mohsen, El-Sayed A. El-Dahshan, and Abdel-Badeeh M. Salem (2011). Comparative Study of Intelligent Classification Techniques for Brain Magnetic Resonance Imaging. International Scientific Conference INFORMATICS 2011, Rožňava, Slovakia, pp.175-178. Link
• Heba Mohsen, El-Sayed A. El-Dahshan, and Abdel-Badeeh M. Salem (2012). A machine learning technique for MRI brain images. The 8th International Conference on Informatics and Systems (INFOS), Cairo, Egypt, BIO-161-BIO-165. Link