Disease complications can alter vascular network morphology and disrupt tissue functioning. Microvascular diseases of the retina are assessed by visual inspection of retinal images, but this can be challenging when diseases exhibit silent symptoms or patients cannot attend in-person meetings. We examine the performance of machine learning algorithms in detecting microvascular disease when trained on statistical and topological summaries of segmented retinal vascular images.

中文翻译：

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统计和拓扑总结有助于分割视网膜血管图像的疾病检测

疾病并发症可以改变血管网络形态并破坏组织功能。视网膜微血管疾病通过视网膜图像的目视检查来评估，但当疾病表现出无症状或患者无法参加面对面的会议时，这可能具有挑战性。当对分割的视网膜血管图像的统计和拓扑摘要进行训练时，我们检查了机器学习算法在检测微血管疾病方面的性能。