Mariotti Letizia, Devaney Nicholas
J Opt Soc Am A Opt Image Sci Vis. 2015 Apr 1;32(4):497-506. doi: 10.1364/JOSAA.32.000497.
Many algorithms have been proposed to help clinicians evaluate cone density and spacing, as these may be related to the onset of retinal diseases. However, there has been no rigorous comparison of the performance of these algorithms. In addition, the performance of such algorithms is typically determined by comparison with human observers. Here we propose a technique to simulate realistic images of the cone mosaic. We use the simulated images to test the performance of three popular cone detection algorithms, and we introduce an algorithm which is used by astronomers to detect stars in astronomical images. We use Free Response Operating Characteristic (FROC) curves to evaluate and compare the performance of the four algorithms. This allows us to optimize the performance of each algorithm. We observe that performance is significantly enhanced by up-sampling the images. We investigate the effect of noise and image quality on cone mosaic parameters estimated using the different algorithms, finding that the estimated regularity is the most sensitive parameter.
已经提出了许多算法来帮助临床医生评估视锥细胞密度和间距，因为这些可能与视网膜疾病的发病有关。然而，尚未对这些算法的性能进行严格比较。此外，此类算法的性能通常通过与人类观察者进行比较来确定。在此，我们提出一种技术来模拟视锥细胞镶嵌的逼真图像。我们使用模拟图像来测试三种流行的视锥细胞检测算法的性能，并引入一种天文学家用于在天文图像中检测恒星的算法。我们使用自由响应操作特征（FROC）曲线来评估和比较这四种算法的性能。这使我们能够优化每种算法的性能。我们观察到通过对图像进行上采样，性能得到了显著提高。我们研究了噪声和图像质量对使用不同算法估计的视锥细胞镶嵌参数的影响，发现估计的规则性是最敏感的参数。
