Yeoh Wee-Soon, Zhang Cishen
Singapore Technologies Electronics (Info-Comm Systems) Pte Ltd, Singapore 609602, Singapore.
IEEE Trans Biomed Eng. 2006 Oct;53(10):2001-7. doi: 10.1109/TBME.2006.881781.
A new medical ultrasound tissue model is considered in this paper, which incorporates random fluctuations of the tissue response and provides more realistic interpretation of the received pulse-echo ultrasound signal. Using this new model, we propose an algorithm for restoration of the degraded ultrasound image. The proposed deconvolution is a modification of the classical regularization technique which combines Wiener filter and the constrained least squares (LS) algorithm for restoration of the ultrasound image. The performance of the algorithm is evaluated based on both the simulated phantom images and real ultrasound radio frequency (RF) data. The results show that the algorithm can provide improved ultrasound imaging performance in terms of the resolution gain. The deconvolved images visually show better resolved tissue structures and reduce speckle, which are confirmed by a medical expert.
本文考虑了一种新的医学超声组织模型，该模型纳入了组织响应的随机波动，并能对接收到的脉冲回波超声信号进行更现实的解释。利用这个新模型，我们提出了一种用于恢复退化超声图像的算法。所提出的去卷积是对经典正则化技术的一种改进，它结合了维纳滤波器和约束最小二乘（LS）算法来恢复超声图像。基于模拟体模图像和实际超声射频（RF）数据对该算法的性能进行了评估。结果表明，该算法在分辨率增益方面能够提供改进的超声成像性能。去卷积后的图像在视觉上显示出组织结构分辨得更好且散斑减少，这得到了医学专家的证实。
