Content based image retrieval of diabetic macular edema images

Colour fundus images play an important role in diagnosing and screening diabetic macular edema (DME). In rural areas, content-based image retrieval (CBIR) might compensate the lack of expert ophthalmologists. In this work, we present a fully automated CBIR system that retrieves fundus images according to their content (quantity and location) of exudates. First, the macula is divided into three concentric regions whose texture discontinuities are used to represent lesion content of the retina. The image-to-image distance measure gives higher weights to lesions closer to the fovea to reflect the severity of the DME. Retrieval results of the system show precision of 79.2%.