Nonparametric surface regression for strain estimation
Nonparametric surface regression for strain estimation
复制标题
用于应变估计的非参数曲面回归
DOI：
--
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
R. Prager
中科院分区：
文献类型：
--
作者：
Je Lindop;Graham M. Treece;A. Gee;R. Prager
超声应变成像通常涉及在从射频超声数据计算出位移测量之后，应用某种形式的平滑滤波来估计梯度(对应于应变)。所有方法都需要在分辨率和精确度之间进行权衡。技术研究往往集中在射频信号处理的各个方面，但平滑方法的不同对整体性能有很大影响。我们介绍了一种非参数回归方法。与其他线性滤波技术相比，它具有更高的图像质量、更大的实际应用通用性和(潜在的)较低的计算成本。通过分析和实验，验证了它的应变成像特性。除了具有统一分辨率的平滑之外，我们还展示了非参数回归可以用于根据数据质量指标自动改变分辨率，从而避免显示图像中的噪声水平的变化。还考虑了与射频信号处理参数的相互作用。这项工作为未来的研究指明了有希望的途径，通过采取整体的算法设计来改善实际应变成像系统的整体性能。
Ultrasonic strain imaging usually involves applying some form of smoothing filter to estimate gradients (corresponding to strains) after displacement measurements have been calculated from RF ultrasound data. All methods involve trade-offs between resolution and accuracy. Technical research often focuses on aspects of the RF signal processing, but differences in the smoothing method have a significant bearing on overall performance. We introduce a nonparametric regression method. Comparing with other linear-filtering techniques, this has advantages of higher image quality, greater versatility for practical applications, and (potentially) low computational cost. Its properties for strain imaging are examined through analysis and experiments. In addition to smoothing with uniform resolution, we demonstrate that nonparametric regression can be used to vary the resolution automatically based on indicators of data quality, thereby avoiding variation in the noise level within the image displayed. Interactions with RF signal processing parameters are also considered. This work indicates promising avenues for future research to improve the overall properties of practical strain imaging systems by taking a holistic approach to algorithm design.
影响因子：
19.7
作者：
Garra, BS;Cespedes, EI;Pennanen, MF
通讯作者：
Pennanen, MF