Can we revitalize interventional healthcare with AI-XR surgical metaverses?

Qayyum, Adnan; Bilal, Muhammad; Hadi, Muhammad; Capik, Paweł; Caputo, Massimo; Vohra, Hunaid; Al-Fuqaha, Ala; Qadir, Junaid

Abstract

Recent advancements in technology, particularly in machine learning (ML), deep learning (DL), and the metaverse, offer great potential for revolutionizing surgical science. The combination of artificial intelligence and extended reality (AI-XR) technologies has the potential to create a surgical metaverse, a virtual environment where surgeries can be planned and performed. This paper aims to provide insight into the various potential applications of an AI-XR surgical metaverse and the challenges that must be addressed to bring its full potential to fruition. It is important for the community to focus on these challenges to fully realize the potential of the AI-XR surgical metaverses. Furthermore, to emphasize the need for secure and robust AI-XR surgical metaverses and to demonstrate the real-world implications of security threats to the AI-XR surgical metaverses, we present a case study in which the "an immersive surgical attack"on incision point localization is performed in the context of preoperative planning in a surgical metaverse.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Proceedings - 2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023
• Start Date: Jun 26, 2023
• End Date: Jun 28, 2023
• Acceptance Date: Apr 14, 2023
• Online Publication Date: Oct 6, 2023
• Publication Date: Oct 20, 2023
• Deposit Date: May 3, 2023
• Publicly Available Date: Oct 7, 2025
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Pages: 496-503
• Book Title: IEEE International Conference on Metaverse Computing, Networking and Applications (IEEE MetaCom 2023)
• ISBN: 9798350333343
• DOI: https://doi.org/10.1109/MetaCom57706.2023.00091
• Keywords: Index Terms-metaverse; augmented reality; mixed reality; virtual reality; surgical science; artificial intelligence
• Public URL: https://uwe-repository.worktribe.com/output/10736691