KneeXNeT - Knee radiographs assessment using Artificial Intelligence (AI)
Over one third of the UK population live with a musculoskeletal condition affecting the joints or spine. Amongst them, osteoarthritis (OA) is one of the common condition that affects joints, in particular the knee joints (due to bearing with the body weight). OA affects around 8.5 million people in the UK.
In the current research, radiographs (X-ray imaging) remain the mainstay of OA progression monitoring as they are accessible, quick, require minimal radiation and are low cost compared to other imaging modalities such Magnetic Resonance Imaging.
Advances in Artificial Intelligence (AI) now open the opportunity to automate assessment of progression of OA on radiographs. Machine Learning, and in particular Deep Learning (DL), has enabled artefact detection, grading medical imaging, and detection of pathological conditions.
The project will aim to investigate the state-of-the-art computer vision object detection methods that could be used for tracking changes in knee X-ray imaging.
The project may also involve modifying the existing object detection methods to implement a bespoke AI/DL model for monitoring radiological changes, and writing up the report with a future publication in mind.
Up to 12 weeks. Primary supervisor available from 19 June 2023
The ideal candidate will have:
- Strong programming skills (preferable Python, or Matlab/C++ and willing to learn Python)
-Experience or interest in machine learning (Deep Learning) and medical image analysis (in particular radiological imaging)
-Experience or enthusiasm to work with clinicians