Knee Osteoarthritis Severity

Assessing knee osteoarthritis (OA) severity accurately is crucial for effective diagnosis and treatment planning, yet current clinical methods suffer from subjectivity and inter-rater variability. Research focuses on developing automated systems using deep learning, employing architectures like convolutional neural networks, Swin Transformers, and diffusion models, often incorporating techniques such as self-supervised learning and domain adaptation to improve accuracy and reduce reliance on large annotated datasets. These advancements aim to provide more objective, reproducible, and potentially continuous measures of OA severity, ultimately improving patient care and informing clinical decision-making.