The Role of Mixed and Augmented Reality in Medical Visualization: Literature Review and A Context-Aware Taxonomy

[2608.27644] The Role of Mixed and Augmented Reality in Medical Visualization: Literature Review and A Context-Aware Taxonomy Skip to main content Search Submit Donate Log in Computer Science > Graphics arXiv:2608.27644 (cs) [Submitted on 27 Aug 2026] Title: The Role of Mixed and Augmented Reality in Medical Visualization: Literature Review and A Context-Aware Taxonomy Authors: Xinrui Zou , Mingxu Liu , Hongchao Shu , Ruixing Liang , Mathias Unberath , Alejandro Martin-Gomez View PDF HTML (experimental) Abstract: The discovery and evolution of medical imaging technologies have enabled non-invasive visualization of internal anatomy that has be- come essential for supporting diagnosis, monitoring, and treatment. However, because medical imaging relies on complex physical processes and contrast mechanisms for image formation, imaging alone is not sufficient to enable humans to leverage the resulting in- formation fully. In addition, traditional methods to visualize the resulting information use two-dimensional displays to present three-dimensional anatomical structures. The introduction of Augmented and Mixed Reality (AR/MR) technologies offers an opportunity to provide valuable paradigms for medical imaging visualization, allowing users to observe, explore, and interact with anatomical infor- mation in more spatially intuitive ways. However, naive implementation without careful design considerations can lead to perceptual inconsistencies, potentially compromising utility and effectiveness. In this paper, we present a structured taxonomy of medical AR/MR visualization strategies aimed at providing clearer insight into how visualization design varies across clinical use cases. The taxonomy organizes techniques based on four core design components: image modality, data dimensionality, display technology, and clinical application. In addition, we introduce two critical dimensions that are often overlooked in the literature: visualization anchoring (the spatial relationship between virtual content and the physical world), and perceptual awareness (the use of visual cues to support spatial interpretation). Together, these components form a comprehensive taxonomy, offering a detailed framework for selecting appropriate visualization techniques in medical applications. Comments: Accepted at IEEE ISMAR 2026. The definitive version will be available in IEEE Xplore Subjects: Graphics (cs.GR) Cite as: arXiv:2608.27644 [cs.GR] (or arXiv:2608.27644v1 [cs.GR] for this version) https://doi.org/10.48550/arXiv.2608.27644 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Xinrui Zou [ view email ] [v1] Thu, 27 Aug 2026 19:32:08 UTC (2,768 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Additional Features Audio Summary Current browse context: cs.GR < prev | next > new | recent | 2026-08 Change to browse by: cs References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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