Longitudinal graph-based segmentation of macular OCT using fundus alignment.
Longitudinal graph-based segmentation of macular OCT using fundus alignment.
复制标题
使用眼底对齐对黄斑 OCT 进行基于纵向图的分割。
DOI：
10.1117/12.2077713
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Prince,JerryL
中科院分区：
文献类型：
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作者：
Lang,Andrew;Carass,Aaron;Al-Louzi,Omar;Bhargava,Pavan;Ying,HowardS;Calabresi,PeterA;Prince,JerryL
光学相干断层扫描（OCT）对视网膜分层的分割已成为多种眼部和神经系统疾病的重要诊断工具。目前，所有OCT分割算法都独立分析数据，忽略了之前的扫描，这可能导致由于算法的可变性和无法识别视网膜层的细微变化而导致的虚假测量。在本文中，我们提出了一个基于图的分割框架，以提供一致的纵向分割结果。随着时间的推移，正则化是通过在每次访问中添加相应体素之间的加权边来完成的。在连接图形之前，我们将扫描对齐到一个共同的主题空间，通过使用低分辨率分割生成的视网膜血管和视网膜厚度注册数据。这种初始分割还允许通过减小图的大小来更有效地解决高维时间问题。验证是在24个受试者的纵向数据上进行的，在那里我们探索我们的纵向图方法和横截面图方法之间的可变性。我们的结果表明，纵向分量提高了分割一致性，特别是在由于扫描质量差而难以可视化边界的区域。
Segmentation of retinal layers in optical coherence tomography (OCT) has become an important diagnostic tool for a variety of ocular and neurological diseases. Currently all OCT segmentation algorithms analyze data independently, ignoring previous scans, which can lead to spurious measurements due to algorithm variability and failure to identify subtle changes in retinal layers. In this paper, we present a graph-based segmentation framework to provide consistent longitudinal segmentation results. Regularization over time is accomplished by adding weighted edges between corresponding voxels at each visit. We align the scans to a common subject space before connecting the graphs by registering the data using both the retinal vasculature and retinal thickness generated from a low resolution segmentation. This initial segmentation also allows the higher dimensional temporal problem to be solved more efficiently by reducing the graph size. Validation is performed on longitudinal data from 24 subjects, where we explore the variability between our longitudinal graph method and a cross-sectional graph approach. Our results demonstrate that the longitudinal component improves segmentation consistency, particularly in areas where the boundaries are difficult to visualize due to poor scan quality.