The CLAP 2027 Challenge focuses on the automated prediction of anatomical landmarks of the hip from pelvic MRI data.
The robust and reliable identification of anatomical landmarks are essential for a variety of computer-assisted orthopaedic surgery applications, such as pre-operative surgical planning, intra-operative navigation, robotic-assisted surgery, patient-specific biomechanical modelling, and implant design.
To support these applications, numerous approaches have been presented to automatically annotate medical images (or derivative formats) with anatomical landmarks. These approaches substantially differ in their underlying methodologies. It is yet unknown, how these approaches perform relative to each other. However, this is highly clinically relevant, as this may affect surgical planning and ultimately decision-making.
The CLAP 2027 Challenge addresses this by collecting multi-centre large-scale hip landmark annotations and benchmarking different prediction methods. The findings are expected to contribute to greater transparency and the development of standards for landmark predictions in computer-assisted orthopaedic surgery.