  Neural segmentation has a great impact on the smooth implementation of local
anesthesia surgery. At present, the network for the segmentation includes U-NET
[1] and SegNet [2]. U-NET network has short training time and less training
parameters, but the depth is not deep enough. SegNet network has deeper
structure, but it needs longer training time, and more training samples. In
this paper, we propose an improved U-NET neural network for the segmentation.
This network deepens the original structure through importing residual network.
Compared with U-NET and SegNet, the improved U-NET network has fewer training
parameters, shorter training time and get a great improvement in segmentation
effect. The improved U-NET network structure has a good application scene in
neural segmentation.
