Segmentation of Foveal Avascular Zone of the Retina Based on Morphological Alternating Sequential Filtering

The non-invasive visualization of retinal microvasculature is a traditional way to diagnose and predict some diseases. The region of foveal avascular zone (FAZ) is an important tool to quantify the macular ischemic with implications in the visual acuity. In this work, we proposed an automatic segmentation of FAZ using high-resolution retinal images captured by a retinography conjugated to Retinal Function Imager (RFI) apparatus. The pixels corresponding to FAZ are automatically detected, segmented and measured (area, perimeter, height and width). The proposed algorithm was tested with 20 images of 10 healthy volunteers, and the results were compared to three manual segmentations. The difference between the software and the manual segmentation was 12.8930% (the mean difference between humans was 7.8288%), and the time of each image segmentation was performed 14.1549 times faster by the computer. The method obtained accuracy of 0.9947, sensitivity of 0.8442, and specificity of 0.9972.