Anaemia detection based on sclera and blood vessel colour estimation

Anaemia is a global public health problem with major consequences for human health. Noninvasive methods must be investigated to determine a sick person's anaemic status or conduct screening campaigns, especially in resource-constrained areas of the earth. This study aims to prove that the colour of the sclera and scleral blood vessels extracted from digital images of the eye can be used to check the anaemic status of a person. To date, we have not found in the literature other studies that have attempted this promising approach. We propose a novel pipeline for anaemia estimation consisting of three main contributions: a sclera segmentation algorithm applied to near-taken digital photos of the eye, a vessel extraction algorithm, and a classifier to predict the anaemic status of a person vs normal controls. This study was based on the public dataset Eyes-defy-anaemia, which contains 218 eye pictures taken with a special device that removes any ambient light influence. Very interesting results have been achieved for the sclera segmentation task with good precision (88.53), recall (82.53) and F1 (84.10). The colour features and haemoglobin value appear to be well related allowing us to obtain an F2 score in the anaemia detection task of 86.4% using colour features from the whole sclera and of 83.8% using only vessels’ colour features.