Graduation Projects
2024
Abstract
Advanced Deep Learning Framework for Accurate Glioblastoma Segmentation in Brain MRI: A Comprehensive Clinical Solution Featured in Cloud-based Zero-Footprint Medical Imaging Platform
Team Members
Mahmoud Yaser
Ibrahim Mohamed
Maha Medhat Fathy
Ahmed Hassan
Mohamed Ismail
Advisors: Dr. Meena M. Makary (Cairo University) & Dr. Mohamed Al-masni (Sejong Univesity) in Collaboration with AIn Shams University Hospital Radiology Dept.
Keywords: Brain Tumor Segmentation, MRI Motion Artifact Correction, Active Learning, Web Development, Computer Vision, Multi Contrast MR, Medical Data Acquisition
Abstract
Representing text in a vectorized form to easily find relationships between documents and rank results for a searching query.
Team Members
Magdy Nasr
Michael Hany
Mohamed Mostafa
Ahmed Emad
Mohab Mohamed
Advisor: Dr. Inas Ahmed Yassine
External Supervisor: Botit
Keywords: Semantic Search Algorithm, Deep Learning, NLP
Abstract
Building an automated deep learning framework for medical imaging segmentation and analysis (such as liver and neuroblastoma), with a focus on running benchmark experiments using various neural networks.
Team Members
Bassant Medhat
Mariam Ahmed
Yousef Adham
Hager Sherif
Mariam Wael
Advisor: Dr. Meena Makary
External Supervisor: Dr. Hossam El-Rewaidy
Keywords: liver and lesions segmentation, Deep learning, multi center dataset,neuroblastoma segmentation, medical viewer website
Abstract
A system that facilitates the generation of technical documents for medical devices, based on standards from organizations like ISO and IEC and other companies’ technical documents.
Team Members
Yehia Said Ahmed
Omar Mustafa
Advisor: Dr. Bassel Tawfik, Dr. Muhammad Rushdi
External Supervisor: Eng. Aya El-Mowafi – Ezz Medical
Keywords: Web Development, Medical Standards, Clinical Enginnering
Abstract
Our aim is to develop personalized real time AI-based knee osteoarthritis system. We use gait metrics measured by IMU sensors to predict the severity and osteoarthritis progression using machine or deep learning algorithms (TBD). Based on detected severity level, guided exercises will be determined for each patient based. Patient progress will be reported to the physician to allow close follow-up.
Team Members
Rahma Abdelkader
Sama Mostafa
Misara Ahmed
Yousr Hejy
Youssef Essam
Keywords:Rehabilitation, Deep Learning, Embedded System, IoT, Mobile application
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A mobile application designed for doctors and patients to diagnose and assess Bell’s Palsy. It uses computer vision and deep learning techniques to identify facial landmarks, making diagnosis more accurate and less subjective, and provide a platform that connects doctors with patients.
Team Members
Amira Mohammed Abdelfattah
Doha Eid
Mariam Mohamed Ezzat
Mayar Ehab
Maye Khaled
Advisor: Dr. Amira Gaber
External Supervisor: UniParticle
Keywords: Mobile App Development, Computer Vision-based DL Modelling, Assistive Technology
Abstract
A deep learning approach to classify the age & predict the shape of the face using NIR dorsal hand veins images
Team Members
Hanya Ahmad Samy
Nourhan Sayed Saad
Mahmoud Rabea
Sohaila Mahmoud
Advisor: Dr. Meena Makary
External Supervisor: Dr. Hossam El-Rewaidy
Keywords: liver and lesions segmentation, Deep learning, multi center dataset,neuroblastoma segmentation, medical viewer website
Abstract
soft active brace for scoliosis with personalized correction force using actuators and force sensor feedback
Team Members
Esraa Ali
Mostafa Mahmoud
Adham mohammed
Mina Fakhry
Advisor: Dr Mohameed Islam
Dr Aliaa Rehan
Keywords: Home-based rehabilitation , Assistive robotic , Embedded systems , IOT
Abstract
Building new model using the combination of Deep learning techniques and algorithms that can theoritically be applied to different type of sequential data(bio-signal,NLP,..) to zero/few shot subsequance matching. testing the results against the benchmark
Team Members
Mina Safwat Samy
Dina Khalid Mohammad Assaeed Salama
Omnia Said Sedik Hassunien
Mohamed Nasser Hussein
Advisor: Dr. Meena Abdelmaseeh
External Supervisor: Dr. Ji / Cacao Systems
Keywords: Algorithms, few-shot learning, continual learning, Subsequence matching, Research
Abstract
An immersive Virtual reality rehabilitation toolkit for patients with upper limb dysfunctions
Team Members
Dina Mostafa Mohamed
Ereny Eleya
Mohamed Salah
Amr Mohamed
Advisor: Dr. Aliaa Rehan
External Supervisor: Dr. Ahmed El Kabbani
Keywords:Hand position, Virtual reality, Rehabilitation
Abstract
Utilizing VR technology to transform the traditional rehabilitation experience by virtualizing Rehacom, an established cognitive training tool. We specifically target divided attention and visuospatial attention.
Team Members
Gehad Ahmed Mohamed
Rawda Yousry Hamda
Rawan Abdelrahman Rashad
Maryam Megahed Gamil
Sara Amgad Helmy
Advisor: Dr. Tamer Basha
External Supervisor: Dr Ahmed El Kabbani
Keywords: Cognitive functions, virtual reality
Abstract
Virtual Reality (VR) technology is proposed for endoscopy training, offering immersive simulations for medical students to practice various scenarios, receive real-time feedback, and enhance learning in a cost-effective and accessible manner.
Team Members
Ghofran Mohamed Suliman
Kareman Yasser Mohamed
Mayar Fayez Sadek
Nada Ahmed Mohamed
Naira Youssef Abdelazim
Advisor: Dr.Ahmed Morsy
Keywords: Endoscopy training by Virtual reality
Abstract
Functional electric stimulation that is controlled by brain signals which classified using AI techniques . A glove equipped with flexsensor is also used for real time feedback
Team Members
Dina Hussam
Sherif Ahmed
Omar Anwar
Omar Saad
Neveen Mohamed
Advisor: Dr. Aliaa Rehan
Keywords: BCI, Rehabilitation, Signal processing, AI, IoT, Embedded systems
Abstract
Breast Cancer Classification and Generation of CESM using deep learning + DICOM web viewer
Team Members
Ahmed Ashraf
Aya Sameh
Aya Amr
Ehab Kamal
Mohamed Hashem
Advisor: Dr. Tamer Basha, Dr. Ahmed Ehab
External Supervisor: Dr. Ahmed Ehab – Astute Imaging
Keywords:Contrast Enhanced Mammography, GANs, Deep Learning, Breast Cancer
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications
Abstract
A Mobile Application Leveraging Deep Learning for Burn Severity Assessment using skin burn images and Enhancing Doctor-Patient Communication
Team Members
Ahmed Mohamed Mahmod Elsarta
Habiba Fathalla Abd Elmoneem
Rawan Mohamed Fekry
Sara Ayman Mohammed
Marina Nasser Fayez
Advisor:Dr. Amira Gaber
External Supervisor:Eng. Maged Eino – EBMES
Keywords:AI, Deep Learning, Databases, Mobile Applications