通过最优整体声速补偿实现高效像差校正
Efficient Aberration Correction via Optimal Bulk Speed of Sound Compensation
AI总结：
本文分析接收波束形成中单一最优整体声速校正的界限，提出基于B模式图像自动识别声速的指标，实验证明其可显著改善分辨率和腹部肝脏图像质量。
摘要：
诊断性超声是腹部检查中一种多功能且实用的工具，对于早期非酒精性脂肪性肝病（NAFLD）的检测和缓解尤为重要。然而，对于NAFLD风险更高的肥胖人群，超声在穿过更厚、声学上非均质的体壁时会发生畸变（像差），导致其性能下降。许多超声像差校正方法需要测量通道数据之间的关系。基于图像本身的更简单的整体声速优化已展示出经验性效果，但其分析局限性尚未得到评估。在本文中，我们从分析角度评估接收波束形成中单一最优声速校正用于校正像差并改善所得图像的界限。此外，我们提出了一种针对求和后B模式图像的客观指标，用于识别该声速，并通过体外仿体实验以及带物理像差层的在体腹部超声数据采集验证该技术。我们发现，对于相关厚度（1至3 cm）和声速（1400至1500 m/s）的层，整体校正可以近似像差剖面。此外，通过体外实验，我们显示分辨率显著改善（平均点目标宽度降低60%），并且利用由波束形成图像自动确定的整体声速校正，在体边界描绘得到改善。总之，我们的结果证明了简单、高效的整体声速校正用于提升诊断性肝脏图像质量的实用性。
英文摘要：
Diagnostic ultrasound is a versatile and practical tool in the abdomen, and is particularly vital toward the detection and mitigation of early-stage non-alcoholic fatty liver disease (NAFLD). However, its performance in those with obesity -- who are at increased risk for NAFLD -- is degraded due to distortions of the ultrasound as it traverses thicker, acoustically heterogeneous body walls (aberration). Many aberration correction methods for ultrasound require measures of channel data relationships. Simpler, bulk speed of sound optimizations based on the image itself have demonstrated empirical efficacy, but their analytical limitations have not been evaluated. Herein, we assess analytically the bounds of a single, optimal speed of sound correction in receive beamforming to correct aberration, and improve the resulting images. Additionally, we propose an objective metric on the post-sum B-mode image to identify this speed of sound, and validate this technique through in virto phantom experiments and in vivo abdominal ultrasound data collection with physical aberrating layers. We find that a bulk correction may approximate the aberration profile for layers of relevant thicknesses (1 to 3 cm) and speeds of sound (1400 to 1500 m/s). Additionally, through in vitro experiments, we show significant improvement in resolution (average point target width reduced by 60 %) and improved boundary delineation in vivo with bulk speed of sound correction determined automatically from the beamformed images. Together, our results demonstrate the utility of simple, efficient bulk speed of sound correction to improve the quality of diagnostic liver images.
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