Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence in Spine Imaging Interpretation
0
Zitationen
10
Autoren
2026
Jahr
Abstract
Spinal disorders, one of the leading causes of disability worldwide, are routinely assessed on imaging studies. Recent advancements in artificial intelligence for spine imaging interpretation may significantly improve diagnostic accuracy and workflow efficiency, using deep learning and conventional machine learning methods. This narrative review focuses on the innovative artificial intelligence applications in spine imaging interpretation with a pathology-based approach: vertebral fractures, spinal deformities, degenerative disease, skeletal tumors, inflammatory disorders, and opportunistic screening. We provide musculoskeletal radiologists with an up-to-date overview of artificial intelligence applications in spine imaging, thus assisting them in an efficient use of these emerging technologies and promoting clinical adoption.
Ähnliche Arbeiten
A survey on deep learning in medical image analysis
2017 · 13.799 Zit.
nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
2020 · 7.936 Zit.
Calculation of average PSNR differences between RD-curves
2001 · 4.093 Zit.
Magnetic Resonance Classification of Lumbar Intervertebral Disc Degeneration
2001 · 3.917 Zit.
Vertebral fracture assessment using a semiquantitative technique
1993 · 3.625 Zit.