Yue Yong, Croitoru Mahai, Bidani Akhil, Zwischenberger Joseph, Clark John W
Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Conf Proc IEEE Eng Med Biol Soc. 2004;2004:1609-12. doi: 10.1109/IEMBS.2004.1403488.
This work proposes a novel speckle suppression method, called robust nonlinear wavelet diffusion. It shows that the log-transformed speckle can be approximated by Gaussian noise contaminated with long burst outliers. Consequently, we exploit this knowledge to design a speckle suppression filter within the framework of wavelet analysis. The outliers are removed by the combination of the robust-residual filter and nonlinear diffusion filter, and the Gaussian noise is eliminated by the wavelet soft-shrinkage technique. We validate the proposed method using synthetic and real echocardiographic images. The performance improvement over other traditional denoising filters is quantified in terms of noise suppression and structural preservation indices. Finally, using the denoised image, we improve the performance of the gradient vector flow snake by modifying its external force field, and we quantify the volume of left ventricle via segmentation applied to the echocardiographic image.
本文提出了一种名为稳健非线性小波扩散的新型散斑抑制方法。研究表明，对数变换后的散斑可由受长脉冲异常值污染的高斯噪声近似表示。因此，我们利用这一知识在小波分析框架内设计了一种散斑抑制滤波器。通过稳健残差滤波器和非线性扩散滤波器的组合去除异常值，并利用小波软阈值技术消除高斯噪声。我们使用合成和真实的超声心动图图像验证了所提出的方法。通过噪声抑制和结构保留指标对该方法相对于其他传统去噪滤波器的性能提升进行了量化。最后，利用去噪后的图像，通过修改其外力场提高了梯度向量流蛇模型的性能，并通过对超声心动图图像进行分割来量化左心室的容积。
