IEEE Trans Med Imaging. 2018 Feb;37(2):580-589. doi: 10.1109/TMI.2017.2767908.
Macular holes are blinding conditions, where a hole develops in the central part of retina, resulting in reduced central vision. The prognosis and treatment options are related to a number of variables, including the macular hole size and shape. High-resolution spectral domain optical coherence tomography allows precise imaging of the macular hole geometry in three dimensions, but the measurement of these by human observers is time-consuming and prone to high inter- and intra-observer variability, being characteristically measured in 2-D rather than 3-D. We introduce several novel techniques to automatically retrieve accurate 3-D measurements of the macular hole, including: surface area, base area, base diameter, top area, top diameter, height, and minimum diameter. Specifically, we introduce a multi-scale 3-D level set segmentation approach based on a state-of-the-art level set method, and we introduce novel curvature-based cutting and 3-D measurement procedures. The algorithm is fully automatic, and we validate our extracted measurements both qualitatively and quantitatively, where our results show the method to be robust across a variety of scenarios. Our automated processes are considered a significant contribution for clinical applications.
黄斑裂孔是一种致盲性疾病，其特征是视网膜中央部分出现孔，导致中心视力下降。预后和治疗选择与许多变量有关，包括黄斑裂孔的大小和形状。高分辨率谱域光学相干断层扫描允许对黄斑裂孔的几何形状进行三维精确成像，但人类观察者的测量既耗时又容易出现高的观察者内和观察者间变异性，通常以二维而不是三维进行测量。我们引入了几种新的技术来自动获取黄斑裂孔的准确三维测量值，包括：表面积、基底面积、基底直径、顶部面积、顶部直径、高度和最小直径。具体来说，我们引入了一种基于最先进水平集方法的多尺度三维水平集分割方法，并且引入了新的基于曲率的切割和三维测量过程。该算法是全自动的，我们对提取的测量值进行了定性和定量验证，结果表明该方法在各种情况下都具有很强的鲁棒性。我们的自动化处理过程被认为是对临床应用的重要贡献。
