Zhang Fan, Yoo Yang Mo, Koh Liang Mong, Kim Yongmin
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
IEEE Trans Med Imaging. 2007 Feb;26(2):200-11. doi: 10.1109/TMI.2006.889735.
A new speckle reduction method, i.e., Laplacian pyramid-based nonlinear diffusion (LPND), is proposed for medical ultrasound imaging. With this method, speckle is removed by nonlinear diffusion filtering of bandpass ultrasound images in Laplacian pyramid domain. For nonlinear diffusion in each pyramid layer, a gradient threshold is automatically determined by a variation of median absolute deviation (MAD) estimator. The performance of the proposed LPND method has been compared with that of other speckle reduction methods, including the recently proposed speckle reducing anisotropic diffusion (SRAD) and nonlinear coherent diffusion (NCD). In simulation and phantom studies, an average gain of 1.55 dB and 1.34 dB in contrast-to-noise ratio was obtained compared to SRAD and NCD, respectively. The visual comparison of despeckled in vivo ultrasound images from liver and carotid artery shows that the proposed LPND method could effectively preserve edges and detailed structures while thoroughly suppressing speckle. These preliminary results indicate that the proposed speckle reduction method could improve image quality and the visibility of small structures and fine details in medical ultrasound imaging.
本文提出了一种新的医学超声成像散斑抑制方法,即基于拉普拉斯金字塔的非线性扩散(LPND)方法。该方法通过在拉普拉斯金字塔域中对带通超声图像进行非线性扩散滤波来去除散斑。对于每个金字塔层中的非线性扩散,通过中值绝对偏差(MAD)估计器的变化自动确定梯度阈值。将所提出的LPND方法的性能与其他散斑抑制方法进行了比较,包括最近提出的散斑减少各向异性扩散(SRAD)和非线性相干扩散(NCD)。在模拟和体模研究中,与SRAD和NCD相比,分别获得了1.55 dB和1.34 dB的平均对比度噪声比增益。对肝脏和颈动脉的体内超声图像去斑后的视觉比较表明,所提出的LPND方法可以有效地保留边缘和详细结构,同时彻底抑制散斑。这些初步结果表明,所提出的散斑抑制方法可以提高医学超声成像中的图像质量以及小结构和精细细节的可见性。