Automated identification of cone photoreceptors in adaptive optics retinal images
Automated identification of cone photoreceptors in adaptive optics retinal images
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DOI：
10.1364/josaa.24.001358
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发表时间：
2007-05-01
影响因子：
1.9
通讯作者：
Roorda, Austin
中科院分区：
文献类型：
--
作者：
Li, Kaccie Y.;Roorda, Austin
在对人体锥体镶嵌体进行无创测量时，标记每个锥体的任务是不可避免的。手动标记是一个耗时的过程，这为开发自动化方法奠定了动力。实现了一种用于在自适应光学 (AO) 视网膜图像中标记视锥细胞的自动算法，并在真实数据上进行了测试。锥体的光纤特性有助于算法的设计。在来自 6 张不同图像的 2153 个手动标记的视锥细胞中，自动化方法正确识别了其中的 94.1%。六幅图像中自动标记方法和手动标记方法之间的一致性从 92.7% 到 96.2% 不等。对于 1.2% 到 9.1% 的视锥细胞，两种方法的结果不一致。对 AO 视网膜图像的大蒙太奇进行 Voronoi 分析，证实了视网膜锥体的一般六边形堆积结构以及视网膜各部分的一般锥体密度变异性。我们测量的一致性证明了针对此问题的自动化解决方案的可靠性和实用性。 (c) 2007 年美国光学学会。
In making noninvasive measurements of the human cone mosaic, the task of labeling each individual cone is unavoidable. Manual labeling is a time-consuming process, setting the motivation for the development of an automated method. An automated algorithm for labeling cones in adaptive optics (AO) retinal images is implemented and tested on real data. The optical fiber properties of cones aided the design of the algorithm. Out of 2153 manually labeled cones from six different images, the automated method correctly identified 94.1% of them. The agreement between the automated and the manual labeling methods varied from 92.7% to 96.2% across the six images. Results between the two methods disagreed for 1.2% to 9.1% of the cones. Voronoi analysis of large montages of AO retinal images confirmed the general hexagonal-packing structure of retinal cones as well as the general cone density variability across portions of the retina. The consistency of our measurements demonstrates the reliability and practicality of having an automated solution to this problem. (c) 2007 Optical Society of America.