Macgillivray T J, Patton N, Doubal F N, Graham C, Wardlaw J M
Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:6456-9. doi: 10.1109/IEMBS.2007.4353837.
Complexity of the retinal vascular network is quantified through the measurement of fractal dimension. A computerized approach enhances and segments the retinal vasculature in digital fundus images with an accuracy of 94% in comparison to the gold standard of manual tracing. Fractal analysis was performed on skeletonized versions of the network in 40 images from a study of stroke. Mean fractal dimension was found to be 1.398 (with standard deviation 0.024) from 20 images of the hypertensives sub-group and 1.408 (with standard deviation 0.025) from 18 images of the non-hypertensives subgroup. No evidence of a significant difference in the results was found for this sample size. However, statistical analysis showed that to detect a significant difference at the level seen in the data would require a larger sample size of 88 per group.
视网膜血管网络的复杂性通过分形维数的测量来量化。一种计算机化方法可增强和分割数字眼底图像中的视网膜血管系统，与手动追踪的金标准相比，准确率达94%。在一项中风研究的40张图像中，对网络的骨架化版本进行了分形分析。在高血压亚组的20张图像中，平均分形维数为1.398（标准差为0.024），在非高血压亚组的18张图像中，平均分形维数为1.408（标准差为0.025）。对于该样本量，未发现结果有显著差异的证据。然而，统计分析表明，要检测出数据中所见水平的显著差异，每组需要更大的样本量88例。
