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Artificial intelligence (AI) is transforming musculoskeletal imaging, particularly in spine imaging. This review explores current AI applications, use cases, and future challenges in optimizing radiology workflows.

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Area of Science:

  • Medical imaging
  • Artificial intelligence in radiology
  • Spine imaging analysis

Background:

  • Clinical applications of artificial intelligence (AI) are increasingly focused on musculoskeletal imaging routines.
  • AI tools are being developed to optimize the radiology value chain in spine imaging across various modalities.
  • The integration of AI presents new opportunities and challenges in diagnostic imaging.

Purpose of the Study:

  • To review the current status of artificial intelligence (AI) utilization in spine imaging.
  • To explore the diverse tasks and use cases for AI applications within spine radiology.
  • To discuss the future perspectives, chances, and challenges of AI-based solutions in daily imaging practice.

Main Methods:

  • Review of recent investigations and existing literature on AI in musculoskeletal and spine imaging.
  • Clarification of fundamental artificial intelligence (AI) concepts relevant to medical imaging.
  • Discussion and illustration of specific AI tasks and use cases in spine imaging.

Main Results:

  • AI applications are being developed to enhance efficiency and accuracy in spine imaging workflows.
  • Identified use cases span various aspects of the radiology value chain, from image acquisition to interpretation.
  • The review synthesizes current AI capabilities and outlines potential future advancements.

Conclusions:

  • Artificial intelligence (AI) holds significant promise for revolutionizing spine imaging by optimizing workflows and potentially improving diagnostic outcomes.
  • Understanding AI concepts and specific applications is crucial for effective integration into clinical practice.
  • Addressing future challenges related to AI implementation, validation, and ethical considerations is essential for realizing its full potential in radiology.