Department of Electrical and Computer Engineering, COMSATS University, Islamabad, Pakistan.
PLoS One. 2020 Jan 30;15(1):e0227566. doi: 10.1371/journal.pone.0227566. eCollection 2020.
Automatic optic disc (OD) localization and segmentation is not a simple process as the OD appearance and size may significantly vary from person to person. This paper presents a novel approach for OD localization and segmentation which is fast as well as robust. In the proposed method, the image is first enhanced by de-hazing and then cropped around the OD region. The cropped image is converted to HSV domain and then V channel is used for OD detection. The vessels are extracted from the Green channel in the cropped region by multi-scale line detector and then removed by the Laplace Transform. Local adaptive thresholding and region growing are applied for binarization. Furthermore, two region properties, eccentricity, and area are then used to detect the true OD region. Finally, ellipse fitting is used to fill the region. Several datasets are used for testing the proposed method. Test results show that the accuracy and sensitivity of the proposed method are much higher than the existing state-of-the-art methods.
自动视盘（OD）定位和分割不是一个简单的过程，因为 OD 的外观和大小可能因人而异而有很大的差异。本文提出了一种快速而鲁棒的 OD 定位和分割的新方法。在提出的方法中，图像首先通过去雾增强，然后在 OD 区域周围裁剪。裁剪后的图像转换为 HSV 域，然后使用 V 通道进行 OD 检测。在裁剪区域中，通过多尺度线检测器提取血管，并通过拉普拉斯变换去除。应用局部自适应阈值和区域生长进行二值化。此外，还使用两个区域属性，即偏心度和面积来检测真实的 OD 区域。最后，使用椭圆拟合来填充区域。使用多个数据集来测试所提出的方法。测试结果表明，所提出的方法的准确性和灵敏度都高于现有的最先进的方法。
