CMF trauma presents significant surgical and diagnostic challenges due to the region’s anatomical complexity and critical functional roles. Recent advances in AI, particularly in machine learning and computer vision, have shown substantial promise in enhancing imaging interpretation, surgical planning, and postoperative outcome simulation. This chapter synthesizes the current landscape of AI applications in CMF trauma surgery, with a focus on imaging analysis, 3D modeling, surgical simulation, decision support systems, and predictive outcome modeling. Real-world case studies illustrate AI’s practical utility, highlight existing limitations, and explore future directions for integrating AI into CMF clinical workflows.

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AI in Surgical Planning and Simulation in Cranio-Maxillofacial Trauma

  • Tuan D. Pham,
  • Simon Holmes,
  • Domniki Chatzopoulou,
  • Paul Coulthard

摘要

CMF trauma presents significant surgical and diagnostic challenges due to the region’s anatomical complexity and critical functional roles. Recent advances in AI, particularly in machine learning and computer vision, have shown substantial promise in enhancing imaging interpretation, surgical planning, and postoperative outcome simulation. This chapter synthesizes the current landscape of AI applications in CMF trauma surgery, with a focus on imaging analysis, 3D modeling, surgical simulation, decision support systems, and predictive outcome modeling. Real-world case studies illustrate AI’s practical utility, highlight existing limitations, and explore future directions for integrating AI into CMF clinical workflows.