[Automatic detection of microaneurysms in colour fundus images].

PURPOSE: We present the development of a tool for the automatic detection of microaneurysms and its clinical evaluation. The intention of this tool is to facilitate the diagnosis of diabetic retinopathy in general screening programs.

METHOD: The designed and developed tool consists of three stages of processing: 1) Obtaining of the basic image of eye with the retinal camera, inverted image on the green channel, and a high-pass filter of the image. This phase enhances the microaneurysms. 2) Detection of the candidates for microaneurysms, by means of an adaptive prediction filter and regions growth. 3) Selection, among the candidates, of whom microaneurysms must be considered to fulfil the criteria of circular shape, high intensity in the inverted green channel and contrasts with respect to the surrounding pixels.

RESULTS: We selected to 20 retinal photographs of good quality and dimensions 600x600 pixels from patients with nonproliferative diabetic retinopathy. The ophthalmologists detected 297 microaneurysms in these images. The tool for automatic detection correctly located 252 microaneurysms, with a mean sensitivity of 89% and a false positives rate of 93%.

CONCLUSIONS: The results obtained seem to indicate that the tool developed will be very useful for its potential use in screening programs in primary care centres. On the other hand, more work is needed on the algorithm to decrease the rate of false positives.