Who we are
- Neill Campbell Computer Scientist
- Tony Shardlow Mathematician
- Will Tillett Consultant Rheumatologist
- Allen Paul PhD student
Recent members
Our mission
To exploit machine-learning methodologies for the effective treatment of rheumatic diseases.
Assessment of joint damage via X-rays is an essential part of treating and diagnosing various types of arthritis. This task is traditionally undertaken by rheumatologists, which is both time consuming and expensive. Improving the assessment of X-rays has huge potential for advancing precision medicine in arthritis treatment including the potential of improving diagnosis and prognosis, understanding which treatments can help prevent damage to joints and improving trial design for novel therapeutic agents.
Publications
- Rambojun, A., Tillett, W., Shardlow, T., & Campbell, N. (2021) Active Latent Space Shape Model: A Bayesian Treatment of Shape Model Adaptation with an Application to Psoriatic Arthritis Radiographs. 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). link
- Rambojun, A. (2020) Automatic Scoring of X-rays in Psoriatic Arthritis (PhD thesis). link
- Rambojun, A.M., Tillett, W., Campbell, N.D.F., & Shardlow, T. (2019) Development of an automated segmentation algorithm to identify bones of the hand. Annals of the Rheumatic Diseases, vol. 78.). link
- Rambojun, A., Tillett, W., Campbell, N.D.F., & Shardlow, T. (2019) A novel human-assisted computer algorithm for identification of hand bones on plain radiographs in psoriatic arthritis. Rheumatology, vol. 58. link
Collaborators
- Pfizer
- Bath Institute for Rheumatic Diseases - BIRD
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath
- Institute of Mathematical Innovation at the University of Bath.
- Royal United Hospital
Software
ASPAX is our annotation tool.