Practical Applications of Artificial Intelligence in Spine Imaging: A Review

Upasana Upadhyay Bharadwaj; Cynthia T Chin; Sharmila Majumdar

doi:10.1016/j.rcl.2023.10.005

Practical Applications of Artificial Intelligence in Spine Imaging: A Review

Radiol Clin North Am. 2024 Mar;62(2):355-370. doi: 10.1016/j.rcl.2023.10.005. Epub 2023 Nov 18.

Authors

Upasana Upadhyay Bharadwaj¹, Cynthia T Chin², Sharmila Majumdar¹

Affiliations

¹ Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, Byers Hall, Suite 203, Room 203D, San Francisco, CA 94158, USA.
² Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143, USA. Electronic address: cynthia.t.chin@ucsf.edu.

PMID: 38272627
DOI: 10.1016/j.rcl.2023.10.005

Abstract

Artificial intelligence (AI), a transformative technology with unprecedented potential in medical imaging, can be applied to various spinal pathologies. AI-based approaches may improve imaging efficiency, diagnostic accuracy, and interpretation, which is essential for positive patient outcomes. This review explores AI algorithms, techniques, and applications in spine imaging, highlighting diagnostic impact and challenges with future directions for integrating AI into spine imaging workflow.

Keywords: Artificial intelligence; Deep learning; Machine learning; Spine.

Publication types

Review

MeSH terms

Algorithms
Artificial Intelligence*
Diagnostic Imaging / methods
Humans
Machine Learning*
Workflow