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UltraRay: Introducing Full-Path Ray Tracing in Physics-Based Ultrasound Simulation

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arxiv 2501.05828 v3 pith:2RP7GAD3 submitted 2025-01-10 cs.CV cs.GR

classification cs.CVcs.GR
keywords ultrasoundpipelinetracingproposedscenesimulationwaveadvanced
verification ladder T0 review T1 audit T2 compute T3 formal
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Traditional ultrasound simulators solve the wave equation to model pressure distribution fields, achieving high accuracy but requiring significant computational time and resources. To address this, ray tracing approaches have been introduced, modeling wave propagation as rays interacting with boundaries and scatterers. However, existing models simplify ray propagation, generating echoes at interaction points without considering return paths to the sensor. This can result in unrealistic artifacts and necessitates careful scene tuning for plausible results. We propose a novel ultrasound simulation pipeline that utilizes a ray tracing algorithm to generate echo data, tracing each ray from the transducer through the scene and back to the sensor. To replicate advanced ultrasound imaging, we introduce a ray emission scheme optimized for plane wave imaging, incorporating delay and steering capabilities. Furthermore, we integrate a standard signal processing pipeline to simulate end-to-end ultrasound image formation. We showcase the efficacy of the proposed pipeline by modeling synthetic scenes featuring highly reflective objects, such as bones. In doing so, our proposed approach, UltraRay, not only enhances the overall visual quality but also improves the realism of the simulated images by accurately capturing secondary reflections and reducing unnatural artifacts. By building on top of a differentiable framework, the proposed pipeline lays the groundwork for a fast and differentiable ultrasound simulation tool necessary for gradient-based optimization, enabling advanced ultrasound beamforming strategies, neural network integration, and accurate inverse scene reconstruction.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound

    cs.RO 2025-07 conditional novelty 6.0 of 10

    SonoGym provides parallel, realistic ultrasound simulation for training RL and imitation-learning agents on robotic orthopedic tasks including navigation, reconstruction, and surgery.

  2. Ultrasound Image Generation using Latent Diffusion Models

    cs.CV 2025-02 conditional novelty 4.0 of 10

    Fine-tuning Stable Diffusion on breast ultrasound images can generate realistic synthetic ultrasound images, and conditioning with segmentation masks via ControlNet gives user control over lesion shape.

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