Entropy thresholding based microaneurysm detection in fundus images

Microaneurysms are small red dots that occur on the retina during preliminary stage of Diabetic Retinopathy. Computer aided microaneurysm screening is necessary to prevent the aggravation of the disease and further vision loss. In this paper, Shannon and Tsallis entropy thresholding in conjunction with Naïve Bayes classifier is suggested for microaneurysm detection. Various shape and intensity based features are extracted to eliminate the falsely detected candidates. The proposed method is evaluated by plotting the FROC curves using the Retinopathy Online Challenge (ROC) and DIARETDB1 databases. The proposed method achieves high sensitivity values of 0.421 and 0.477 (at false positive rate of 8) using Shannon and Tsallis entropy thresholding which is better than some existing methods.