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Artificial Intelligence (AI)-Enhanced Simulation of Facial Filler Sequencing.

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Area of Science:

  • Plastic Surgery
  • Medical Simulation
  • Artificial Intelligence

Background:

  • Preprocedural simulation is crucial for patient counseling and expectation management in plastic surgery.
  • Current simulation technologies often involve expensive 3D imaging systems.
  • Artificial intelligence (AI) is increasingly adopted in plastic surgery but underutilized in preprocedural simulation.

Purpose of the Study:

  • To assess the feasibility of using AI for simulating whole-face rejuvenation with soft tissue fillers.
  • To explore AI's potential as an inexpensive and accessible preprocedural simulation tool.

Main Methods:

  • Utilized AI "generative fill" technology to simulate soft tissue filler injections.
  • Applied AI to alter and rejuvenate specific areas of real patient photographs.
  • Performed whole-face rejuvenation simulations on patient images.

Main Results:

  • Demonstrated the feasibility of using AI for simulating whole-face rejuvenation.
  • AI generative fill technology can realistically alter patient photographs for simulation.
  • AI offers a potentially inexpensive alternative to traditional simulation methods.

Conclusions:

  • AI generative fill technology shows promise for preprocedural simulation in plastic surgery.
  • This study establishes a foundation for future research using advanced AI models in simulation.
  • AI can enhance patient counseling and expectation setting through realistic visual simulations.