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GPU volume rendering in 3D echocardiography: Real-time pre-processing and ray-casting

机译:3D超声心动图中的GPU体积渲染:实时预处理和射线投射

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Since real-time acquisition of 3D echocardiographic data is achievable in practice, many volume rendering algorithms have been proposed for visualization purposes. However, due to the large amounts of data and computations involved a tradeoff between image quality and computational efficiency has to be made. The main goal of our study was to generate high quality volume renderings in real-time, by implementing preprocessing and ray-casting algorithms directly on the GPU. Furthermore the advantage of combining a-priori anatomic and functional information with the volume rendered image was also investigated. The proposed algorithms were implemented both in CUDA and OpenCL and validated on patient datasets acquired using a GE Vivid7 Dimensions system. Assuming a 512×512 pixels output resolution, average running times of 4.2 ms/frame are achievable on high-end graphics systems. Furthermore a good correspondence between wall thickening and segmental longitudinal strain values was visually observed. By implementing ray-casting on the GPU, the overall processing time is significantly reduced, thus making real-time interactive 3D volume rendering feasible. Combining anatomical and functional information allows for a quick visual assessment of a given case.
机译:由于在实践中可以实时采集3D超声心动图数据,因此提出了许多用于可视化目的的体绘制算法。但是,由于涉及大量数据和计算,因此必须在图像质量和计算效率之间进行权衡。我们研究的主要目标是通过直接在GPU上实现预处理和光线投射算法来实时生成高质量的体绘制。此外,还研究了将先验解剖学信息和功能信息与体绘制图像相结合的优势。所提出的算法在CUDA和OpenCL中均已实现,并在使用GE Vivid7 Dimensions系统获取的患者数据集中进行了验证。假设输出分辨率为512×512像素,则高端图形系统的平均运行时间为4.2 ms /帧。此外,在视觉上观察到壁增厚和分段纵向应变值之间的良好对应关系。通过在GPU上实现光线投射,可以显着减少整体处理时间,从而使实时交互式3D体绘制成为可能。结合解剖学信息和功能信息,可以对给定病例进行快速的视觉评估。

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