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.