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Automated segmentation of outer retinal layers in macular OCT images of patients with retinitis pigmentosa

机译:色素性视网膜炎患者黄斑OCT图像中视网膜外层的自动分割

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摘要

To provide a tool for quantifying the effects of retinitis pigmentosa (RP) seen on spectral domain optical coherence tomography images, an automated layer segmentation algorithm was developed. This algorithm, based on dual-gradient information and a shortest path search strategy, delineates the inner limiting membrane and three outer retinal boundaries in optical coherence tomography images from RP patients. In addition, an automated inner segment (IS)/outer segment (OS) contour detection method based on the segmentation results is proposed to quantify the locus of points at which the OS thickness goes to zero in a 3D volume scan. The segmentation algorithm and the IS/OS contour were validated with manual segmentation data. The segmentation and IS/OS contour results on repeated measures showed good within-day repeatability, while the results on data acquired on average 22.5 months afterward demonstrated a possible means to follow disease progression. In particular, the automatically generated IS/OS contour provided a possible objective structural marker for RP progression.
机译:为了提供一种用于量化在光谱域光学相干断层扫描图像上看到的色素性视网膜炎(RP)效果的工具,开发了一种自动层分割算法。该算法基于双梯度信息和最短路径搜索策略,在RP患者的光学相干断层扫描图像中描绘了内部限制膜和三个外部视网膜边界。此外,提出了一种基于分割结果的自动内段(IS)/外段(OS)轮廓检测方法,以量化3D体积扫描中OS厚度变为零的点的轨迹。使用手动分割数据验证了分割算法和IS / OS轮廓。重复测量的分割和IS / OS轮廓结果显示出良好的日内可重复性,而平均之后22.5个月获得的数据结果证明了追踪疾病进展的可能方法。特别是,自动生成的IS / OS轮廓为RP的发展提供了可能的客观结构标记。

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