Leila Hassanlou

Leila holds a Bachelor's degree in Electrical Engineering (Electronics) from Urmia University and a Master's degree in Biomedical Engineering from the University of Tabriz, Iran. Her academic path reflects a transition from electrical engineering toward biomedical applications, with specialized training in medical image processing and computational analysis for clinical diagnosis.

Currently enrolled in a dual-degree doctoral program between the University of Oulu (Medical Physics and Technology) and Lund University (Medical Science, Orthopaedics). Leila's research focuses on machine learning for MRI-based medical image analysis and clinical epidemiology. Her doctoral project aims to develop MRI-based biomarkers for the early detection of knee osteoarthritis following anterior cruciate ligament injury.

Research Focus

Her research investigates early structural changes in bone and cartilage that occur after ACL injury, applying machine learning methods to identify patterns predictive of osteoarthritis development. Through her mobility periods at Lund University, she is gaining specialized expertise in osteoarthritis epidemiology, longitudinal patient cohort analysis, and advanced statistical methods.

The overarching goal of her work is to advance early diagnostic capabilities for post-traumatic osteoarthritis, enabling earlier detection and informing the development of preventive treatment strategies in musculoskeletal medicine.

Her areas of expertise include deep learning, computer vision, and medical image processing with application to orthopedic imaging.