Morphological Exudate Detection in Retinal Images using PCA-based Optic Disc Removal

Diabetic retinopathy lesion detection such as exudate in fundus image of retina can lead to the early diagnosis of the disease. Retinal image includes dark areas such as the main blood vessels and the retinal tissue and also the bright areas such as optic disk, optical fibers, and lesions, e.g. exudate. In this paper, a multi-stage algorithm is proposed for the detection of exudate in foreground. The algorithm segments the background dark areas in the proper channels of RGB color space using morphological processing such as closing, opening, and top-hat operations. Then an appropriate edge detector discriminates between exudates and cotton-like spots or other artificial effects. To tackle the problem of optical fibers and to discriminate between these brightness and exudates, the main vessels are detected from the green channel of RGB color space. Then the optical fiber areas around the vessels are marked up. An algorithm that uses PCA-based reconstruction error is proposed to discard another fundus bright structure named optic disk. Several experiments have been performed with HEI-MED standard database and evaluated by comparing with ground truth images. These results show that the proposed algorithm has a detection accuracy of 96%.