论文标题
通过独立组件分析实现平面波超声波束
Plane-Wave Ultrasound Beamforming Through Independent Component Analysis
论文作者
论文摘要
平面波成像（PWI）中的波束形成是创建具有最佳质量图像的重要步骤。自适应方法估计了几个换能器元素获得的回声痕迹的垂直权重。本文中，我们将平面波束成型为盲源分离问题。每个传感器元件的输出被认为是对场的非独立观察。因此，可以将波束形成作为对观测值的独立组分的估计。然后，我们调整独立组件分析（ICA）算法来解决此问题并重建最终图像。根据Medical Ultrasound的PWI挑战可获得的一组模拟，实际幻影和体内数据评估所提出的方法。还在不同的成像设置中评估了提出的波束形成方法的性能。与经典延迟和总和相比，拟议的算法将横向分辨率提高了多达$ 36.5 \％$，并且对比$ 10 \％$。此外，将结果与其他众所周知的自适应方法进行了比较。最后，研究了提出的噪声方法的鲁棒性。
Beamforming in plane-wave imaging (PWI) is an essential step in creating images with optimal quality. Adaptive methods estimate the apodization weights from echo traces acquired by several transducer elements. Herein, we formulate plane-wave beamforming as a blind source separation problem. The output of each transducer element is considered as a non-independent observation of the field. As such, beamforming can be formulated as the estimation of an independent component out of the observations. We then adapt the independent component analysis (ICA) algorithm to solve this problem and reconstruct the final image. The proposed method is evaluated on a set of simulation, real phantom, and in vivo data available from the PWI challenge in medical ultrasound. The performance of the proposed beamforming approach is also evaluated in different imaging settings. The proposed algorithm improves lateral resolution by as much as $36.5\%$ and contrast by $10\%$ as compared to the classical delay and sum. Moreover, results are compared with other well-known adaptive methods. Finally, the robustness of the proposed method to noise is investigated.
