IJCAI 2024poster6 citations

AI-Enhanced Virtual Reality in Medicine: A Comprehensive Survey

Yixuan Wu, Kaiyuan Hu, Danny Z. Chen, Jian Wu

Abstract

With the rapid advance of computer graphics and artificial intelligence technologies, the ways we interact with the world have undergone a transformative shift. Virtual Reality (VR) technology, aided by artificial intelligence (AI), has emerged as a dominant interaction media in multiple application areas, thanks to its advantage of providing users with immersive experiences. Among those applications, medicine is considered one of the most promising areas. In this paper, we present a comprehensive examination of the burgeoning field of AI-enhanced VR applications in medical care and services. By introducing a systematic taxonomy, we meticulously classify the pertinent techniques and applications into three well-defined categories based on different phases of medical diagnosis and treatment: Visualization Enhancement, VR-related Medical Data Processing, and VR-assisted Intervention. This categorization enables a structured exploration of the diverse roles that AI-powered VR plays in the medical domain, providing a framework for a more comprehensive understanding and evaluation of these technologies.nTo our best knowledge, this work is the first systematic survey of AI-powered VR systems in medical settings, laying a foundation for future research in this interdisciplinary domain.

Multidisciplinary Topics and Applications: MTA: Health and medicineComputer Vision: CV: 3D computer visionComputer Vision: CV: Action and behavior recognitionComputer Vision: CV: ApplicationsComputer Vision: CV: Biomedical image analysisComputer Vision: CV: Motion and trackingComputer Vision: CV: Recognition (object detection, categorization)Computer Vision: CV: Scene analysis and understandingComputer Vision: CV: SegmentationMultidisciplinary Topics and Applications: MTA: Real-time systems
BibTeX
@inproceedings{ijcai2024p920,
  title     = {AI-Enhanced Virtual Reality in Medicine: A Comprehensive Survey},
  author    = {Wu, Yixuan and Hu, Kaiyuan and Chen, Danny Z. and Wu, Jian},
  booktitle = {Proceedings of the Thirty-Third International Joint Conference on
               Artificial Intelligence, {IJCAI-24}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Kate Larson},
  pages     = {8326--8334},
  year      = {2024},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2024/920},
  url       = {https://doi.org/10.24963/ijcai.2024/920},
}