基于各向异性扩散方程的超声图像去噪与边缘增强

Anisotropic Diffusion Equation Based Ultrasonic Image Denoising and Edge Enhancement

超声图像利用不同组织和局部细节的不同回声信号强度和分布来捕捉重要的医学病变信息.然而,超声图像在形成过程中产生的斑点噪声使得超声图像质量较差,给以后的图像特征提取和识别,病情诊断及定量分析造成不利的影响.本文利用局部坐标变换,边缘、局部细节的一、二阶法向导数和双曲正切函数,结合各向异性扩散方程,提出了一种超声图像去噪与边缘增强算法:可以在去除噪声的同时,保持重要的边缘、局部细节和超声回声亮条.理论分析和实验结果表明了本文算法的有效性.

Utilizing the echoic intension and distribution of different organizations and local details, ultrasonic image catches the important medical pathological changes. However ultrasonic image may be contaminated by the speckle noise in its forming process, which degrades image quality specially concealing some details, and works disadvantages to image segmentation, character extraction and image recognition, disease diagnosis and quantitative analysis.Using local coordinate transform, the first and second order normal derivatives of edge and local detail and the hyperbolic tangent function, also combining the anisotropic diffusion equation, we have put forth an ultrasonic image denoising and edge enhancement scheme, which can preserve edges, local details and ultrasonic echoic bright strips on denoising. This has been indicated theoretically and experimentally.