摘要：The early signs of diabetic retinopathy (DR) are depicted by
microaneurysms among other signs. A prompt diagnosis when the
disease is at the early stage can help prevent irreversible
damages to the diabetic eye. In this paper, we propose a decision
support system (DSS) for automated screening of early signs of
diabetic retinopathy. Classification schemes for deducing the
presence or absence of DR are developed and tested. The detection
rule is based on binary-hypothesis testing problem which
simplifies the problem to yes/no decisions. An analysis of the
performance of the Bayes optimality criteria applied to DR is also
presented. The proposed DSS is evaluated on the real-world data.
The results suggest that by biasing the classifier towards DR
detection, it is possible to make the classifier achieve good
sensitivity.
