#computer vision

AI motion capture system for enhancing human motor function
This project aims to advance the field of human movement science by addressing the challenges encountered when developing a low-cost, automated system for screening the movement of pre-elite student-athletes. Leveraging state-of-the-art artificial intelligence (AI), markerless motion capture and stereo vision technologies, this research will tackle critical challenges in biomechanics and sports science.

Synthetic CT via Generative AI for MR-guided Radiotherapy Planning in the Abdomen and Lungs
This Project will leverage artificial intelligence to develop and validate synthetic computed tomography (CT) from magnetic resonance imaging (MRI) in the abdominal and lung regions. The expected outcomes are an AI-based synthetic CT model, thorough technical and clinical validation and potential patent/licensing opportunities. This may reduce unnecessary ionising radiation of CT in patients and improve treatment efficiency during radiotherapy planning.

Evaluating Robotic Medical Surgery with Multimodal and Responsible AI
This Project aims to develop multimodal and responsible artificial intelligence (AI) for automated robotic surgery assessment. The expected outcome is to develop multimodal and responsible AI for automated robotic surgery assessment. The potential benefit is enhanced surgical training, improved patient outcomes, reduced training costs, and increased transparency.