PANDORA has three primary advantages over alternative approaches. First, it both detects the presence of PPA and allows quantification of the PPA region automatically from 2-D color fundus images alone. Previous studies6,28 were limited to the detection of PPA. Conventionally, the size of the PPA region is quantified manually.2,39 PANDORA therefore provides the first automated tool to allow PPA development to be tracked. Second, PANDORA improves upon our previous tool14,20 by using an OD segmentation approach based on an edge map, which estimates the OD/PPA boundary more accurately. Therefore, it can describe the actual shape of the regions, allowing more detailed study of the relationship between PPA and different ocular diseases. The previous approach, which was based on the ‘snake’ algorithm, suffered from a random offset in defining the boundary and could give only an estimate of the size. Third, PANDORA has been fully automated, reducing the dependency on a human assessor and minimizing problems related to human errors such as habituation. PANDORA’s physiological measurements offer additional information for clinicians studying ophthalmic or systemic diseases. Fourth, PANDORA is intrinsically more appropriate for large-scale screening programs owing to the utilization of a 2-D fundus camera as an alternative to the OCT equipment. A digital fundus camera40 could acquire fundus images quickly, without the time-consuming scanning procedure required by the OCT machine. It is also relatively cheap and has become a standard examination tool in ophthalmology clinics. Therefore, working on 2-D fundus images is both cost-effective and time-effective, and it is more convenient to the users as compared with OCT instruments.