Broadly, my research focuses on leveraging the latest advances in computer vision to build tools which are clinically useful. Over the course of my PhD, this has been mostly related disease classification in spinal MRIs. Other topics I have worked on include: self-supervised learning (MICCAI '21), multi-modal learning (MICCAI '21) and segmentation (MedNeurips '21).
3D Spinal Column Segmentation with Single Plane 2D-Projected Annotations
Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman
Medical Imaging meets NeurIPS 2021
Machine Learning Based Berlin Scoring Of Magnetic Resonance Images of the Spine in Patients with Ankylosing Spondylitis from the Measure 1 Study
Amir Jamaludin, Rhydian Windsor, Sarim Ather, Timor Kadir, Andrew Zisserman, Jürgen Braun, Lianne S Gensler, Pedro M Machado, Mikkel Østergaard, Denis Poddubnyy, Thibaud Coroller, Brian Porter, Shepard Mpofu, Aimee Readie
European League Against Rheumatism (EULAR) 2020
Machine Learning Based Berlin Scoring Of Magnetic Resonance Images of the Spine in Patients with Ankylosing Spondylitis: Analysis of Data from a Phase 3 Trial with Secukinumab
Amir Jamaludin, Rhydian Windsor, Sarim Ather, Timor Kadir, Andrew Zisserman, Jürgen Braun, Lianne S Gensler, Pedro M Machado, Mikkel Østergaard, Denis Poddubnyy, Thibaud Coroller, Brian Porter, Shepard Mpofu, Aimee Readie
American College of Rheumatology Convergence (ACR) 2020
A Novel Methodology To Differentiate Shrinkage Versus Erosion in CBCT Images of Lung Cancer Tumours
George Needham*, Rhydian Windsor*, William Beasley, Marcel van Herk, Eliana Vasquez Osorio, Marianne Aznar, Alan McWilliam
European Conference Of Medical Physics (ECMP) 2018
Best Poster Award