White matter lesion (WML) is one of the common cerebral abnormalities, it indicates changes in the white matter of human brain and have shown significant association with stroke, dementia and deaths. Magnetic resonance imaging (MRI) of the brain is frequently used to diagnose white matter lesion (WML) volume. Regular screening can detect WML in early stage and save from severe consequences. Current option of MRI based diagnosis is impractical for regular screening because of its high expense and unavailability. Thus, earlier screening and prediction of the WML volume/load specially in the rural and remote areas becomes extremely difficult. Research has shown that changes in the retinal micro vascular system reflect changes in the cerebral micro vascular system. Using this information, we have proposed a retinal image based WML volume and severity prediction model which is very convenient and easy to operate.

中文翻译：

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一种新的视网膜血管特征和基于机器学习的脑白质病变预测模型

白质病变（WML）是常见的大脑异常之一，它表明人类大脑白质的变化，并与中风、痴呆和死亡显着相关。大脑的磁共振成像 (MRI) 经常用于诊断白质病变 (WML) 体积。定期筛查可以及早发现 WML，避免严重后果。目前基于 MRI 的诊断选择对于定期筛查来说是不切实际的，因为其费用高昂且不可用。因此，特别是在农村和偏远地区，早期筛选和预测 WML 容量/负载变得非常困难。研究表明，视网膜微血管系统的变化反映了脑微血管系统的变化。使用这些信息，