Joint segmentation and classification of retinal arteries/veins from fundus images.

•A fast deep-learning method that simultaneously segments and classifies vessels into arteries and veins is proposed.•An efficient graph-based method is used to propagate the CNN's labeling through the vascular tree.•Our method outperforms the leading previous works on a public dataset for A/V classification and is by far the fastest.•The proposed global arterio-venous ratio (AVR) calculated on the whole fundus image using our automatic A/V segmentation method can better track vessel changes associated to diabetic retinopathy than the standard local AVR.