Current status and future prospects of artificial intelligence in musculoskeletal imaging
YUAN Huishu
NI Ming
Abstract：Musculoskeletal disorders are characterized by diverse pathological types and complex anatomical structures,placing high demands on the precision of imaging examinations.In recent years,artificial intelligence(AI)has shown great potential in musculoskeletal imaging,particularly in anatomical segmentation,lesion detection,quantitative measurement,and intelligent diagnosis.This review systematically summarizes advances in AI applications for degenerative joint diseases,sports injuries,fracture detection,osteoporosis screening,and musculoskeletal tumors,while also outlining its expanding roles in image reconstruction,quality control,and educational support.Furthermore,it highlights the developmental trends of large AI models in musculoskeletal imaging and discusses their potential and challenges in multimodal,multitask,and personalized clinical decision support.Although AI has reached or even surpassed expert-level performance in certain tasks,limitations remain in model generalization,data acquisition and annotation standards,cross-modality integration,and clinical adaptability.Future progress will require high-quality data construction,interdisciplinary collaboration,and the establishment of standardized frameworks to advance musculoskeletal AI toward more intelligent,efficient,and standardized clinical practice.
Keywords：Musculoskeletal systemImagingArtificial intelligenceDiagnosis
Publication Date：2025-09-15
Online Publishing Date：2025-10-13(First online date of this platform, not the publication date of the document)
Pages：7( 497-503 )