n order to reduce the labor and timeintensive burden of manually marking arteries and veins, an algorithm for automatic segmentation of retinal arteries and veins based on the ResNet_UNet network model is proposed in this research. First, retinal images were acquired using a multispectral retinal imaging system and a dataset was made. The dataset contained 206 retinal fundus images at 548 nm wavelength and their pixellevel labels. Then, the multiscale feature extraction module and loss function module in the ResNet_UNet network model were optimized. And a channel attention mechanism and postprocessing methods were added to improve the accuracy of automatic classification of arteries and veins. Finally, 165 images were randomly selected from the dataset as the training set, and 41 images were tested as the test set. Experiments show that the deep learning model established in this study can automatically and accurately segment the arteries and veins in retinal images, with an accuracy rate of 98.50%. Keywords：