标题： UltraRay：增强超声模拟真实感的全路径光线追踪 显示英文标题

标题： UltraRay: Full-Path Ray Tracing for Enhancing Realism in Ultrasound Simulation

摘要： 传统的超声波模拟器通过求解波动方程来模拟压力分布场，实现了高精度但需要大量的计算时间和资源。 为了解决这个问题，引入了射线追踪方法，将波传播建模为与边界和散射体相互作用的射线。 然而，现有的模型简化了射线传播，在交互点生成回波而不考虑返回传感器的路径。 这可能导致不真实的伪影，并且需要仔细调整场景以获得合理的结果。 我们提出了一种新的超声波模拟流程，利用射线追踪算法生成回波数据，追踪每条射线从换能器经过场景并返回传感器的路径。 为了复制先进的超声波成像，我们引入了一种针对平面波成像优化的射线发射方案，包含了延迟和波束控制能力。 此外，我们集成了一个标准的信号处理流程，以模拟端到端的超声波图像形成。 我们通过建模包含高度反射物体（如骨骼）的合成场景来展示所提出流程的有效性。 在此过程中，我们提出的方案UltraRay不仅提高了整体视觉质量，还通过准确捕捉二次反射并减少不自然的伪影，提高了模拟图像的真实性。 通过建立在可微框架之上，所提出的流程为一种快速且可微的超声波模拟工具奠定了基础，这对于基于梯度的优化是必要的，能够实现先进的超声波波束成形策略、神经网络集成和精确的逆场景重建。 显示英文摘要

摘要： 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.