Winners of the 2024 MICCAI landmark detection challenge.
Research Experience
I lead the Oxford Medical Image Science (OxMedIS) group, which works across x-ray, MRI, CT, ultrasound, and other imaging data. We design algorithms that detect and classify clinically relevant features, reconstruct anatomical structures in 3D, and provide tools that balance automation with clinician input. Beyond image analysis, we address failure detection and model calibration to ensure reliability, with the ultimate goal of translating these methods into clinical practice.
Background
My research develops machine learning methods for medical image analysis, including segmentation, 3D reconstruction, and anatomical landmark detection. Current projects integrate multi-modality data to improve diagnostic accuracy, while ensuring trust and fairness in healthcare AI.