Martinez-Perez M Elena, Witt Nicholas, Parker Kim H, Hughes Alun D, Thom Simon A M
Institute of Research on Applied Mathematics and Systems, Department of Computer Science, Universidad Nacional Autónoma de México, Mexico City, Mexico.
National Heart & Lung Institute, Imperial College, London, UK.
PeerJ. 2019 Jun 27;7:e7119. doi: 10.7717/peerj.7119. eCollection 2019.
The optic disc (OD) in retinal fundus images is widely used as a reference in computer-based systems for the measurement of the severity of retinal disease. A number of algorithms have been published in the past 5 years to locate and measure the OD in digital fundus images. Our proposed algorithm, automatically: (i) uses the three channels (RGB) of the digital colour image to locate the region of interest (ROI) where the OD lies, (ii) measures the Shannon information content per channel in the ROI, to decide which channel is most appropriate for searching for the OD centre using the circular Hough transform. A series of evaluations were undertaken to test our hypothesis that using the three channels gives a better performance than a single channel. Three different databases were used for evaluation purposes with a total of 2,371 colour images giving a misdetection error of 3% in the localisation of the centre of the OD. We find that the area determined by our algorithm which assumes that the OD is circular, is similar to that found by other algorithms that detected the shape of the OD. Five metrics were measured for comparison with other recent studies. Combining the two databases where expert delineation of the OD is available (1,240 images), the average results for our multispectral algorithm are: TPR = 0.879, FPR = 0.003, Accuracy = 0.994, Overlap = 80.6% and Dice index = 0.878.
视网膜眼底图像中的视盘（OD）在基于计算机的系统中被广泛用作衡量视网膜疾病严重程度的参考。在过去5年里，已经发表了许多算法来定位和测量数字眼底图像中的视盘。我们提出的算法能够自动：（i）利用数字彩色图像的三个通道（RGB）来定位视盘所在的感兴趣区域（ROI）；（ii）测量感兴趣区域中每个通道的香农信息含量，以确定使用圆形霍夫变换搜索视盘中心时哪个通道最合适。我们进行了一系列评估，以检验我们的假设，即使用三个通道比使用单个通道性能更好。为了评估目的，使用了三个不同的数据库，共有2371幅彩色图像，视盘中心定位的误检误差为3%。我们发现，我们的算法所确定的假定视盘为圆形的区域，与其他检测视盘形状的算法所发现的区域相似。测量了五个指标以与其他近期研究进行比较。结合有视盘专家划定区域的两个数据库（1240幅图像），我们的多光谱算法的平均结果为：真阳性率（TPR）=0.879，假阳性率（FPR）=0.003，准确率（Accuracy）=0.994，重叠率（Overlap）=80.6%，骰子系数（Dice index）=0.878。
