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Computational Medical Extended Reality ( CMXR ), brings together life sciences and neuroscience with mathematics, engineering, and computer science. It unifies computational science (scientific computing) with intelligent extended reality and spatial computing for the medical field. It significantly differs from previous “Clinical XR” and “Medical XR” terms, as it is focusing on how to integrate computational methods from neural simulation to computational geometry, computational vision and computer graphics with deep learning models to solve hard problems in medicine and neuroscience: from low-code/no-code/genAI authoring platforms to deep learning XR systems for training, planning, real-time operative navigation, therapeutics, and rehabilitation.

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A Computational Medical XR Discipline

  • 会议论文

  • 发表日期：

    2025年

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  • George Papagiannakis,
  • Walter Greenleaf,
  • Michael Cole,
  • Mark Zhang,
  • Rabi Datta,
  • Mathias Delahaye,
  • Eleni Grigoriou,
  • Manos Kamarianakis,
  • Antonis Protopsaltis,
  • Philippe Bijlenga,
  • Nadia Magnenat Thalmann,
  • Eleftherios Tsiridis,
  • Eustathios Kenanidis,
  • Kyriakos Vamvakidis,
  • Ioannis Koutelidakis,
  • Oliver A. Kannape

摘要

Computational Medical Extended Reality ( CMXR ), brings together life sciences and neuroscience with mathematics, engineering, and computer science. It unifies computational science (scientific computing) with intelligent extended reality and spatial computing for the medical field. It significantly differs from previous “Clinical XR” and “Medical XR” terms, as it is focusing on how to integrate computational methods from neural simulation to computational geometry, computational vision and computer graphics with deep learning models to solve hard problems in medicine and neuroscience: from low-code/no-code/genAI authoring platforms to deep learning XR systems for training, planning, real-time operative navigation, therapeutics, and rehabilitation.