ClipGS-VR: Immersive and Interactive Cinematic Visualization of Volumetric Medical Data in Mobile Virtual Reality
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2026
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866911402278518784 |
|---|---|
| author | Tong, Yuqi Li, Ruiyang Li, Chengkun Liu, Qixuan Qiu, Shi Heng, Pheng-Ann |
| author_facet | Tong, Yuqi Li, Ruiyang Li, Chengkun Liu, Qixuan Qiu, Shi Heng, Pheng-Ann |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_19310 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | ClipGS-VR: Immersive and Interactive Cinematic Visualization of Volumetric Medical Data in Mobile Virtual Reality Tong, Yuqi Li, Ruiyang Li, Chengkun Liu, Qixuan Qiu, Shi Heng, Pheng-Ann Graphics Human-Computer Interaction 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. |
| title | ClipGS-VR: Immersive and Interactive Cinematic Visualization of Volumetric Medical Data in Mobile Virtual Reality |
| topic | Graphics Human-Computer Interaction |
| url | https://arxiv.org/abs/2601.19310 |