Zhang Qi, Han Hong, Ji Chunhong, Yu Jinhua, Wang Yuanyuan, Wang Wenping
J Opt Soc Am A Opt Image Sci Vis. 2014 Jun 1;31(6):1273-83. doi: 10.1364/JOSAA.31.001273.
In ultrasound (US), optical coherence tomography, synthetic aperture radar, and other coherent imaging systems, images are corrupted by multiplicative speckle noise that obscures image interpretation. An anisotropic diffusion (AD) method based on the Gabor transform, named Gabor-based anisotropic diffusion (GAD), is presented to suppress speckle in medical ultrasonography. First, an edge detector using the Gabor transform is proposed to capture directionality of tissue edges and discriminate edges from noise. Then the edge detector is embedded into the partial differential equation of AD to guide the diffusion process and iteratively denoise images. To enhance GAD's adaptability, parameters controlling diffusion are determined from a fully formed speckle region that is automatically detected. We evaluate the GAD on synthetic US images simulated with three models and clinical images acquired in vivo. Compared with seven existing speckle reduction methods, the GAD is superior to other methods in terms of noise reduction and detail preservation.
在超声（US）、光学相干断层扫描、合成孔径雷达及其他相干成像系统中，图像会受到乘性散斑噪声的干扰，从而影响图像解读。本文提出了一种基于伽柏（Gabor）变换的各向异性扩散（AD）方法，即基于伽柏的各向异性扩散（GAD），用于抑制医学超声中的散斑。首先，提出一种利用伽柏变换的边缘检测器，以捕捉组织边缘的方向性并区分边缘与噪声。然后将该边缘检测器嵌入到AD的偏微分方程中，以引导扩散过程并对图像进行迭代去噪。为提高GAD的适应性，控制扩散的参数由自动检测到的完整散斑区域确定。我们在三种模型模拟的合成超声图像及体内采集的临床图像上对GAD进行了评估。与七种现有的散斑减少方法相比，GAD在降噪和细节保留方面优于其他方法。
