3 papers
cs.CV2026
A Systematic Benchmark of Intensity Normalisation Methods for 3D Knee MRI Segmentation and Cross-Domain Generalisability
Oliver Mills, Philip Conaghan, Samuel Relton
Robust out-of-the-box performance is essential for the clinical deployment of deep learning models in medical imaging. An important but underexplored factor affecting model general…
eess.IV2025
Putting the Segment Anything Model to the Test with 3D Knee MRI - A Comparison with State-of-the-Art Performance
Oliver Mills, Philip Conaghan, Nishant Ravikumar +1
Menisci are cartilaginous tissue found within the knee that contribute to joint lubrication and weight dispersal. Damage to menisci can lead to onset and progression of knee osteoa…
cs.LG2024
Developing the Temporal Graph Convolutional Neural Network Model to Predict Hip Replacement using Electronic Health Records
Zoe Hancox, Sarah R. Kingsbury, Andrew Clegg +2
Background: Hip replacement procedures improve patient lives by relieving pain and restoring mobility. Predicting hip replacement in advance could reduce pain by enabling timely in…