Oregon Health and Science University, Casey Eye Institute, 3375 NW Terwilliger Boulevard, Portland, Oregon 97239, United States.
Oregon Health and Science University, Casey Eye Institute, 3375 NW Terwilliger Boulevard, Portland, Oregon 97239, United StatesbSoutheast University, Laboratory of Image Science and Technology, Department of Computer Science and Engineering, No. 2 Sipailo.
J Biomed Opt. 2016 Jul 1;21(7):76010. doi: 10.1117/1.JBO.21.7.076010.
Quantification of choroidal neovascularization (CNV) as visualized by optical coherence tomography angiography (OCTA) may have importance clinically when diagnosing or tracking disease. Here, we present an automated algorithm to quantify the vessel skeleton of CNV as vessel length. Initial segmentation of the CNV on en face angiograms was achieved using saliency-based detection and thresholding. A level set method was then used to refine vessel edges. Finally, a skeleton algorithm was applied to identify vessel centerlines. The algorithm was tested on nine OCTA scans from participants with CNV and comparisons of the algorithm’s output to manual delineation showed good agreement.
光学相干断层扫描血管造影（OCTA）显示脉络膜新生血管（CNV）的量化在诊断或跟踪疾病时可能具有重要的临床意义。在这里，我们提出了一种自动算法来量化 CNV 的血管骨架作为血管长度。使用基于显著度的检测和阈值处理对面血管造影上的 CNV 进行初始分割。然后使用水平集方法细化血管边缘。最后，应用骨架算法识别血管中心线。该算法在 9 例 CNV 患者的 OCTA 扫描中进行了测试，并且将算法的输出与手动描绘进行比较，结果显示出良好的一致性。
