  The detection of retinal blood vessels, especially the changes of small
vessel condition is the most important indicator to identify the vascular
network of the human body. Existing techniques focused mainly on shape of the
large vessels, which is not appropriate for the disconnected small and isolated
vessels. Paying attention to the low contrast small blood vessel in fundus
region, first time we proposed to combine graph based smoothing regularizer
with the loss function in the U-net framework. The proposed regularizer treated
the image as two graphs by calculating the graph laplacians on vessel regions
and the background regions on the image. The potential of the proposed graph
based smoothing regularizer in reconstructing small vessel is compared over the
classical U-net with or without regularizer. Numerical and visual results shows
that our developed regularizer proved its effectiveness in segmenting the small
vessels and reconnecting the fragmented retinal blood vessels.
