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Done By: Department of Biomedical Engineering
Post Date: 2024-08-29
Last Browse: 2025-01-15
The Master's student Ghufran Basim Mudib from the Department of Biomedical Engineering successfully defended her thesis on Thursday, August 29, 2024. Her thesis is titled: "Automated Detection of Thyroid Nodule in Ultrasound Imaging Using Artificial Intelligence Network." The defense committee was chaired by Assistant Professor Dr. Ali Majid Hassan from Al-Nahrain University, College of Medicine, and included members Assistant Professor Dr. Ikhlas Kazem Hamza from the University of Technology, Control and Systems Engineering, and Assistant Professor Dr. Aseel Mohammed Ali Hussein from Al-Nahrain University, Biomedical Engineering. The thesis was supervised by Assistant Professor Dr. Hadeel Qasim Wadi from Al-Nahrain University, Biomedical Engineering, and Dr. Khalil Akish Hadi from the Medical City Department, Radiology Institute. The thesis was scientifically evaluated by the first scientific evaluator, Professor Dr. Sadiq Kamel Gharkan from the College of Electrical Engineering Technology at the Middle Technical University, and the second scientific evaluator, Assistant Professor Dr. Mohammed Sabah Jergis from the College of Engineering Technology at the Northern Technical University. The language evaluation was conducted by Dr. Alaa Ayed Jabir from the Biomedical Engineering Department at Al-Nahrain University. The research aims to design intelligent systems for detecting thyroid nodules in ultrasound images and classifying them as benign or malignant, helping radiologists improve the accuracy and efficiency of detecting these nodules. This would alleviate the workload in Iraqi hospitals by enabling a larger number of patients to be examined in a very short time. The research involved using Python programming to design eight models based on deep learning, machine learning, and feature selection techniques. These models were tested on 240 images collected from the Medical City Department, Radiology Institute, proving the models' effectiveness in screening any data from ultrasound devices. The thesis was accepted as it met the requirements for obtaining a Master's degree.