The Department of Biomedical Engineering at the College of Engineering, Al‑Nahrain University held the Master’s thesis defense of student Mahmoud Muhannad Abdul Mahdi on Sunday, March 8, 2026, for his thesis entitled:

“A Deep Learning-Based Framework for Automated Assessment of Knee Alignment for Long Leg Radiographs.”

The examination committee consisted of:

• Prof. Dr. Ali Majid Hassan – Chair
  (College of Medicine – Al‑Nahrain University)

• Asst. Prof. Dr. Aseel Mohammed Ali Hussein – Member
  (College of Engineering – Al‑Nahrain University)

• Consultant Orthopedic Surgeon Dr. Anis Adel Taha – Member
  (Specialized Surgery Hospital – Medical City)

• Asst. Prof. Dr. Sadiq Jaafar Abbas – Member and Supervisor
  (College of Engineering – Al‑Nahrain University)

• Consultant Orthopedic Surgeon Asst. Prof. Dr. Mahmoud Shehab Wahab – Member and Supervisor
  (Al-Kindy College of Medicine – University of Baghdad)

The thesis aims to develop a deep learning–based framework to automate the measurement of knee alignment angles in the frontal plane using long-leg radiographs. The proposed approach integrates multiple stages of medical image processing, object detection models, and keypoint detection algorithms to accurately identify anatomical landmarks and compute alignment angles.

The results demonstrated that the proposed system achieves high accuracy, reliability, and reproducibility in measuring key knee alignment angles. The framework can therefore serve as a supportive clinical tool for orthopedic surgical decision-making.

The thesis was approved as fulfilling the requirements for the Master’s degree in Biomedical Engineering.