Automated Brain Tumor Detection and Classification in MRI Scans Using AI
Supervisor Name
Samah Alaydi
Supervisor Email
salaydi@birzeit.edu
University
Birzeit
Research field
Artificial Intelligence
Bio
Samah Kareem Al Aydi has a Ph.D. in computer engineering from ISIK University in Istanbul, specializing in AI-driven regulatory compliance and deep learning applications. She holds a Master’s in Computer Science from Al Quds University, where her thesis focused on image retrieval using Arabic ontology. Samah is currently a lecturer at Birzeit University and has served as ICT Standardization Research Chairman at the Palestine Standards Institution, working closely with international bodies such as ISO and SMIIC. Her research includes machine-readable standards (ISO SMART) and religious image classification using deep learning models. She is also a country researcher for the Global Index on Responsible AI and has extensive experience in AI, quality systems, and digital regulation.
This project aims to develop an automated deep learning model that assists radiologists in accurately detecting and classifying brain tumors in MRI scans. The approach combines advanced preprocessing techniques (such as skull stripping and intensity normalization) with convolutional neural networks (CNNs) to enhance diagnostic accuracy and stability. Additionally, the project integrates Grad-CAM (Gradient-weighted Class Activation Mapping) to improve explainability and trust by providing visual heatmaps that highlight the critical areas of MRI scans influencing the AI’s decisions. Through this combination, the system will not only provide high performance in tumor detection but also offer transparent and interpretable results that medical professionals can rely on.
