Segmentation of retinal ganglion cells from fluorescent microscopy imaging

The visual information processing starts in the retina. The working mechanisms of its complex stratified circuits, in which ganglion cells play a central role, is still largely unknown. Understanding the visual coding is a challenging and active research area also requiring automated analysis of retinal images. It demands appropriate algorithms and methods for studying a network population of strictly entangled cells. Within this framework, we propose a combined technique for segmenting retinal ganglion cell (RGC) bodies, the output elements of the retina. The method incorporates a blob enhancement filtering in order to select the specific cell shapes, an active contour process for precise border segmentation and a watershed transform step which separates single cell contours in possible grouped segmentations. The proposed approach has been validated on fluorescent microscopy images of mouse retinas with promising results.