A Mixed-Reality Approach to Cardiovascular Anatomy Education

Mixed-reality (MR) technologies have enhanced anatomy education through immersive three-dimensional visualization; however, most existing systems lack tutoring capabilities that respond contextually during anatomical exploration. This paper presents a reproducible MR anatomy learning platform implemented on the Apple Vision Pro that integrates the open-source Z-Anatomy atlas, with cardiovascular anatomy as the case domain. The system supports interactive exploration through hand gestures and eye tracking, alongside natural-language voice interaction. To provide context-grounded tutoring, we incorporate a retrieval-augmented generation (RAG) voice assistant whose responses are bounded by the Terminologia Anatomica knowledge base and weighted by the learner’s current spatial focus, with spatially anchored labels supporting contextual understanding. The platform was profiled on Apple Vision Pro hardware using Xcode Instruments and exercised through scenario-based walkthroughs of representative anatomical exploration tasks; the system met its real-time interaction and rendering thresholds across eight integrated anatomical systems. By leveraging open-source content and a substitutable AI backend, the architecture reduces software-licensing and development costs by an estimated one to two orders of magnitude relative to comparable proprietary systems and ports across XR platforms via a single bridge layer.