Prompting with the human-touch: evaluating model-sensitivity of foundation models for musculoskeletal CT segmentation

Researchers evaluated 11 promptable foundation models for medical CT image segmentation across bone and implant identification tasks. The study found significant performance variations between models and strategies, with all models showing sensitivity to human prompt variations, suggesting current benchmarks may overestimate real-world performance.