FactorSplat: Appearance-Controllable Gaussian Proxies for Medical Volume Rendering
cs.CV
Submitted: 2026-10-01
Updated: 2026-10-01
Project page: https://gaozhongpai.github.io/FactorSplat
License: http://creativecommons.org/licenses/by/4.0/
The gist: Transfer functions (TFs) control color and visibility in medical volume rendering, but image-trained Gaussian proxies typically bake one transfer function into their appearance.
Abstract
Transfer functions (TFs) control color and visibility in medical volume rendering, but image-trained Gaussian proxies typically bake one transfer function into their appearance. We present FactorSplat, a per-scene N-dimensional Gaussian splatting (N-DGS) proxy that accepts region-specific intensity-to-RGBA curves at inference. A local lookup applies the authored color and opacity change, while a shared functional encoder and low-rank per-Gaussian factors learn the residual appearance response. Geometry and directional appearance remain shared across presets, with visibility control and TF-aware pruning preserving the ability to hide and reveal structures. On seven CT and MR scans, FactorSplat improves mean PSNR and changed-region error over region-aware VEG across validation, interpolation, unseen composition, and out-of-distribution (OOD) edits. Across these four splits, seven-scan mean PSNR gains over VEG range from 1.10 to 1.52 dB. One checkpoint per scan supports unseen edits without retraining. At 1600 squared, the cached fast renderer averages 524 FPS with 1.17 ms TF switches. Project page: https://gaozhongpai.github.io/FactorSplat/.
Sources
- Render-FM: Feedforward Model for Real-time Photorealistic Volumetric Rendering
- Text-based Transfer Function Design for Semantic Volume Rendering
- 3D Gaussian Splatting for Scientific Particle Data Compression and Rendering
- GS-Surrogate: Deformable Gaussian Splatting for Parameter Space Exploration of Ensemble Simulations
- Universal Beta Splatting
- Application of 3D Gaussian Splatting for Cinematic Anatomy on Consumer Class Devices
- ECoNGS: Efficient Compressive Neural Gaussian Splats for Volume Visualization
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