ClipGS-VR: Immersive and Interactive Cinematic Visualization of Volumetric Medical Data in Mobile Virtual Reality
Yuqi Tong, Ruiyang Li, Chengkun Li, Qixuan Liu, Shi Qiu, Pheng-Ann Heng

TL;DR
ClipGS-VR advances mobile VR medical visualization by enabling real-time, high-fidelity, arbitrary-angle slicing of volumetric data through a novel neural inference restructuring and gradient-based opacity modulation.
Contribution
We introduce ClipGS-VR, a novel framework that restructures neural inference for real-time, interactive, high-fidelity volumetric medical visualization in mobile VR with arbitrary-angle slicing.
Findings
Maintains visual fidelity comparable to offline rendering.
Enables smooth, arbitrary-angle slicing in mobile VR.
Offers improved usability and interaction efficiency.
Abstract
High-fidelity cinematic medical visualization on mobile virtual reality (VR) remains challenging. Although ClipGS enables cross-sectional exploration via 3D Gaussian Splatting, it lacks arbitrary-angle slicing on consumer-grade VR headsets. To achieve real-time interactive performance, we introduce ClipGS-VR and restructure ClipGS's neural inference into a consolidated dataset, integrating high-fidelity layers from multiple pre-computed slicing states into a unified rendering structure. Our framework further supports arbitrary-angle slicing via gradient-based opacity modulation for smooth, visually coherent rendering. Evaluations confirm our approach maintains visual fidelity comparable to offline results while offering superior usability and interaction efficiency.
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Taxonomy
TopicsComputer Graphics and Visualization Techniques · Virtual Reality Applications and Impacts · Generative Adversarial Networks and Image Synthesis
