The Master’s thesis entitled “Automated Detection and Diagnosis of Human Brain Tumor using Machine Learning” was defended at the College of Computer Science and Information Technology at the University of Karbala. The student, Sara Ali Abdul-Hussein, presented her thesis on Thursday, February 1, 2024, at 9:30 AM. The defense took place in the Khawarizmi Hall at the College, with the presence of Dr. Muafaq Kazem Al-Hasnawi, the Dean, and several researchers and faculty members.

The study focused on the automated detection and diagnosis of human brain tumors using Machine Learning. The researcher developed a new model capable of detecting tumors using region-based segmentation and edge-based segmentation techniques on magnetic resonance imaging (MRI) images of four different types of human brain tumors: pituitary gland tumor, glioblastoma, meningioma, and normal cases. Four traditional classifiers were employed: Naive Bayes, Random Forest (RF), Decision Tree (DT), and Support Vector Machine (SVM) along with Convolutional Neural Network (CNN) using the VGG16 model.

The examination committee consisted of Prof. Buhija Khudair Shakir, University of Karbala, College of Computer Science and Information Technology, as the chairman, Dr. Skeena Hassan Hashim, University of Technology, Computer Science Department, as a member, Dr. Ashwaan Anwar Abdul-Munim, University of Karbala, College of Computer Science and Information Technology, as a member, and Dr. Alham Mohammed Thabit Abdul Amir, University of Karbala, College of Computer Science and Information Technology, as a member and supervisor. The defense concluded successfully, and Sara Ali Abdul-Hussein was awarded the Master’s degree.