Szkulmowski Maciej, Wojtkowski Maciej, Sikorski Bartosz, Bajraszewski Tomasz, Srinivasan Vivek J, Szkulmowska Anna, Kałuzny Jakub J, Fujimoto James G, Kowalczyk Andrzej
Nicolaus Copernicus University, Institute of Physics, ul. Grudziadzka 5/7, PL-87-100 Toruń, Poland.
J Biomed Opt. 2007 Jul-Aug;12(4):041207. doi: 10.1117/1.2771569.
We present a computationally efficient, semiautomated method for analysis of posterior retinal layers in three-dimensional (3-D) images obtained by spectral optical coherence tomography (SOCT). The method consists of two steps: segmentation of posterior retinal layers and analysis of their thickness and distance from an outer retinal contour (ORC), which is introduced to approximate the normal position of external interface of the healthy retinal pigment epithelium (RPE). The algorithm is shown to effectively segment posterior retina by classifying every pixel in the SOCT tomogram using the similarity of its surroundings to a reference set of model pixels from user-selected area(s). Operator intervention is required to assess the quality of segmentation. Thickness and distance maps from the segmented layers and their analysis are presented for healthy and pathological retinas.
我们提出了一种计算效率高的半自动方法，用于分析通过光谱光学相干断层扫描（SOCT）获得的三维（3-D）图像中的视网膜后层。该方法包括两个步骤：视网膜后层分割以及分析其厚度和与视网膜外轮廓（ORC）的距离，引入ORC是为了近似健康视网膜色素上皮（RPE）外部界面的正常位置。通过使用SOCT断层图像中每个像素与其周围环境与用户选择区域的模型像素参考集的相似性对其进行分类，该算法被证明能有效地分割视网膜后层。需要操作人员干预来评估分割质量。给出了健康和病理视网膜分割层的厚度和距离图及其分析结果。
