IEEE J Biomed Health Inform. 2020 Apr;24(4):1125-1136. doi: 10.1109/JBHI.2019.2929842. Epub 2019 Jul 19.
The presence of hyperreflective foci (HFs) is related to retinal disease progression, and the quantity has proven to be a prognostic factor of visual and anatomical outcome in various retinal diseases. However, lack of efficient quantitative tools for evaluating the HFs has deprived ophthalmologist of assessing the volume of HFs. For this reason, we propose an automated quantification algorithm to segment and quantify HFs in spectral domain optical coherence tomography (SD-OCT). The proposed algorithm consists of two parallel processes namely: region of interest (ROI) generation and HFs estimation. To generate the ROI, we use morphological reconstruction to obtain the reconstructed image and histogram constructed for data distributions and clustering. In parallel, we estimate the HFs by extracting the extremal regions from the connected regions obtained from a component tree. Finally, both the ROI and the HFs estimation process are merged to obtain the segmented HFs. The proposed algorithm was tested on 40 3D SD-OCT volumes from 40 patients diagnosed with non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR), and diabetic macular edema (DME). The average dice similarity coefficient (DSC) and correlation coefficient (r) are 69.70%, 0.99 for NPDR, 70.31%, 0.99 for PDR, and 71.30%, 0.99 for DME, respectively. The proposed algorithm can provide ophthalmologist with good HFs quantitative information, such as volume, size, and location of the HFs.
存在强反射焦点 (HFs) 与视网膜疾病进展有关，其数量已被证明是各种视网膜疾病视觉和解剖结果的预后因素。然而，缺乏有效的 HF 定量工具，使眼科医生无法评估 HF 的体积。出于这个原因，我们提出了一种自动量化算法，用于分割和量化频域光相干断层扫描 (SD-OCT) 中的 HF。所提出的算法由两个并行过程组成，即：感兴趣区域 (ROI) 生成和 HF 估计。为了生成 ROI，我们使用形态重建来获得重建图像和用于数据分布和聚类的直方图。同时，我们通过从连通区域中提取极值区域来估计 HF，该连通区域来自组件树。最后，将 ROI 和 HF 估计过程合并以获得分割的 HF。该算法在 40 名患有非增生性糖尿病视网膜病变 (NPDR)、增生性糖尿病视网膜病变 (PDR) 和糖尿病性黄斑水肿 (DME) 的患者的 40 个 3D SD-OCT 体积上进行了测试。NPDR 的平均骰子相似系数 (DSC) 和相关系数 (r) 分别为 69.70%、0.99，PDR 为 70.31%、0.99，DME 为 71.30%、0.99。该算法可以为眼科医生提供 HF 的定量信息，例如 HF 的体积、大小和位置。
