实时全体积行列成像实时成像
概括
本研究介绍了GPU加速体积束成型,用于使用行列定位数组 (RCAs) 的实时3D超声波成像. 优化的算法实现了高率,使消费者硬件具有先进的成像功能.
科学领域:
- 医疗成像医学成像
- 超声波技术 超声波技术 超声波技术
- 计算成像技术的成像
背景情况:
- 卷度超声波成像传统上需要大量的计算资源.
- 实时3D成像对于许多临床应用至关重要,但通常受到处理速度的限制.
- 排列列列地址阵列 (RCAs) 提供了先进超声波的潜力,但需要高效的光束成形.
研究的目的:
- 在图形处理单元 (GPU) 上实现和优化RCAs的体积束成型.
- 用消费级GPU展示实时3D超声波成像能力.
- 评估拟议的GPU光束成形方法的性能和效率.
主要方法:
- 使用可分离的光束成形算法,将计算负载减少每体积65倍.
- 优化包括在相邻的像素和之间重复使用计算和样本.
- 波束转换器是用CUDA C++实现的,并在NVIDIA GeForce RTX 4090,2080 Ti和3090 GPU上进行了测试.
主要成果:
- 该GPU光束制造器实现了每秒1440个体积的处理速度,明显超过实时要求 (≥12kHz发射率).
- 该系统实现了理论GPU浮点吞吐量的22%.
- 实时3D成像使用标准超声波扫描仪和单一显卡进行了演示.
结论:
- 通过GPU加速的体积光束成型,可以实时使用RCAs进行3D超声波成像.
- 优化的方法显著降低了计算复杂性,使先进的成像可访问.
- 这项技术为具有成本效益的,高性能的3D超声波系统铺平了道路,与2D设置相匹配.
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