Automated layer segmentation of macular OCT images using dual-scale gradient information.
Automated layer segmentation of macular OCT images using dual-scale gradient information.
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DOI：
10.1364/oe.18.021293
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发表时间：
2010-09-27
期刊：
影响因子：
3.8
通讯作者：
Chan K
中科院分区：
文献类型：
--
作者：
Yang Q;Reisman CA;Wang Z;Fukuma Y;Hangai M;Yoshimura N;Tomidokoro A;Araie M;Raza AS;Hood DC;Chan K
提出了一种新的自动边界分割算法，用于快速、可靠地量化光学相干断层扫描（OCT）图像中的九个视网膜内边界。该算法采用两步分割模式的基础上的梯度信息在双尺度上，同时利用局部和互补的全局梯度信息。应用最短路径搜索来优化边缘选择。通过独立手动分割和再现性研究验证了分割算法。它在分割正常的3D OCT体积方面表现出较高的准确性和再现性。每个体积（480×512×128体素）的执行时间约为16秒。该算法也显示出量化患病视网膜图像的潜力。
A novel automated boundary segmentation algorithm is proposed for fast and reliable quantification of nine intra-retinal boundaries in optical coherence tomography (OCT) images. The algorithm employs a two-step segmentation schema based on gradient information in dual scales, utilizing local and complementary global gradient information simultaneously. A shortest path search is applied to optimize the edge selection. The segmentation algorithm was validated with independent manual segmentation and a reproducibility study. It demonstrates high accuracy and reproducibility in segmenting normal 3D OCT volumes. The execution time is about 16 seconds per volume (480×512×128 voxels). The algorithm shows potential for quantifying images from diseased retinas as well.