Retinal vessels are easily and non-invasively imaged using fundus cameras. Growing evidence including longitudinal evidence, suggests morphological changes in retinal vessels are early physio-markers of cardio-metabolic risk and outcome (as well as other disease processes). However, data from large population based studies are needed to examine the nature of these morphological associations. Several retinal image analysis (RIA) systems have been developed. While these provide a number of retinal vessel indices, they are often restricted in the area of analysis, and have limited automation, including the ability to distinguish between arterioles and venules. With the aim of developing reliable, automated, efficient retinal image analysis (RIA) software, generating a rich quantification of retinal vastulature in large volumes of fundus images, we present QUARTZ (Quantitative Analysis of Retinal Vessel Topology and size), a novel automated system for processing and analysing retinal images. QUARTZ consists of modules for vessel segmentation, width measurement and angular change at each vessel centreline pixel with sub-pixel accuracy, computing local vessel orientation, optic disc localisation, arteriole/venule classification, tortuosity measurement, and exporting the quantitative measurements in various output file formats. The performance metrics of the algorithms incorporated in QUARTZ are validated on a number of publically available retinal databases (including DRIVE, STARE, CHASE_DB1, INSPIRE-AVR, and DIARETDB1). QUARTZ performs well in terms of segmentation accuracy, calibre measurement, optic disc and arteriole/venule recognition. The system provides a rich quantification of retinal vessel morphology, which has potential medical applications in identifying those at high risk, so that prophylactic measure can be initiated before onset of overt disease. (C) 2015 Elsevier Ltd. All rights reserved.
