光学相干层析图像层状结构的增强与定量测量

光学相干层析(OCT)成像技术对于眼底等层状组织的定量测量有赖于光学相干层析图像中层状结构的提取。为了对原始光学相干层析图像进行预处理以有效地去除图像中的噪声及散斑、增强图中的层状结构,并更好地保护图像中的层状结构,进而更准确地定量测量图像中有重要意义的层状结构的光程信息,提出在相干增强各向异性扩散(CED)算法中引入二阶导数项以控制沿相干方向的扩散强度,并将引入二阶导数项的相干增强各向异性扩散算法应用于不同样品的光学相干层析图像。结合在预处理后图像中层状结构位置的查找结果与样品的折射率信息,实现了对光学相干层析图像中有重要意义的层状结构厚度的定量测量。实验结果表明,使用引入二阶导数项的相干增强各向异性扩散算法对光学相干层析图像预处理有利于对图中重要层状结构的更准确测量。

Enhancement and Quantitative Measurement of Layer Structures in Optical Coherence Tomographic Images

The quantitative measurements of layer tissues,such as eyeground,in optical coherence tomographic (OCT) imaging depend on the extraction of layer structures.The second derivative item is introduced to control diffusion along coherence orientation in coherence enhancing diffusion algorithm (CED).The method is expected to preprocess the original optical coherence tomographic images to remove noise and speckle,enhance and protect the layer structure,and realize more accurate quantitative measurement for the significant layer structure of images. The coherence enhancing diffusion algorithm with a second derivative item is used in optical coherence tomographic images for different samples.The quantitative measurement for the thickness of significant layer structures in optical coherence tomographic images is done,by combining the location of the layer structure and sample refractivity information in the preprocessed images.Experimental results show that it is helpful to preprocess the optical coherence tomographic images with the modified algorithm for more accurate measurement of significant layer structures.