UltraG-Ray: Physics-Based Gaussian Ray Casting for Novel Ultrasound View Synthesis
Felix Duelmer, Jakob Klaushofer, Magdalena Wysocki, Nassir Navab, Mohammad Farid Azampour

TL;DR
UltraG-Ray introduces a physics-based Gaussian ray casting method for ultrasound view synthesis, improving realism by explicitly modeling tissue effects and view-dependent attenuation.
Contribution
It proposes a learnable 3D Gaussian scene representation combined with a physics-based ray casting scheme for more realistic ultrasound image synthesis.
Findings
Achieves up to 15% increase in MS-SSIM over state-of-the-art methods.
Captures view-dependent attenuation effects naturally.
Produces more realistic B-mode ultrasound images.
Abstract
Novel view synthesis (NVS) in ultrasound has gained attention as a technique for generating anatomically plausible views beyond the acquired frames, offering new capabilities for training clinicians or data augmentation. However, current methods struggle with complex tissue and view-dependent acoustic effects. Physics-based NVS aims to address these limitations by including the ultrasound image formation process into the simulation. Recent approaches combine a learnable implicit scene representation with an ultrasound-specific rendering module, yet a substantial gap between simulation and reality remains. In this work, we introduce UltraG-Ray, a novel ultrasound scene representation based on a learnable 3D Gaussian field, coupled to an efficient physics-based module for B-mode synthesis. We explicitly encode ultrasound-specific parameters, such as attenuation and reflection, into a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
