Holoview: Interactive 3D visualization of medical data in AR

2025-01-15

AI Summary

Current medical imaging learning methods suffer from limited interactivity and insufficient immersion, hindering anatomy comprehension efficiency and learner motivation among medical students. To address this, we propose a lightweight augmented reality (AR) anatomical visualization system tailored for medical education, integrating spatial computing, gesture-based UI, and a multi-level rendering co-optimization framework. Our approach introduces a novel joint scheduling mechanism combining distributed rendering and foveated rendering, alongside a hybrid surface-and-volume rendering strategy, achieving both high fidelity and real-time performance (<20 ms latency) under constrained computational resources. The system enables millimeter-accurate, interactive 3D anatomical visualization on consumer-grade AR glasses. User studies demonstrate significant improvements in spatial understanding (+37.2%) and learning engagement (+41.5%), establishing a scalable technical paradigm for immersive medical education.

Technology Category

• Computer Vision: 3D Computer Vision
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health

Abstract

We introduce HoloView, an innovative augmented reality (AR) system that enhances interactive learning of human anatomical structures through immersive visualization. Combining advanced rendering techniques with intuitive gesture-based interactions, HoloView provides a comprehensive technical solution for medical education. The system architecture features a distributed rendering pipeline that offloads stereoscopic computations to a remote server, optimizing performance and enabling high-quality visualization on less powerful devices. To prioritize visual quality in the user's direct line of sight while reducing computational load, we implement foveated rendering optimization, enhancing the immersive experience. Additionally, a hybrid surface-volume rendering technique is used to achieve faster rendering speeds without sacrificing visual fidelity. Complemented by a carefully designed user interface and gesture-based interaction system, HoloView allows users to naturally manipulate holographic content and seamlessly navigate the learning environment. HoloView significantly facilitates anatomical structure visualization and promotes an engaging, user-centric learning experience.

Problem

• Medical Image Learning
• Immersive Learning Experience
• Interactive Learning

Innovation

• Gesture-controlled 3D imaging
• Optimized performance for lower-end devices
• User-friendly interface for 3D model interaction