The distortion of retinal images is mostly caused by blurred and uneve n illumination.In order to study the effects of different distortion types and different distortion levels on blo od vessel segmentation,this paper quantifies the distortion type and distortion level of the image into the accura cy of image segmentation.Low distortion or uneven distortion images,constructs a database of reti nal distortion images,including 2distortion types,each distortion type has 8levels of distortion,a total of 552distorted retina images,and the accuracy of each distorted image as the label of the image.In addition,a no-r eference quality evaluation method for retinal images based on blood vessel segmentation is proposed,and the quali ty of the final retinal image is obtained by extracting the statistical features of the pixel value of the retina image,the texture features of the image and the shape features of the blood vessel.The test results on the propos ed database show that Pearson product-moment correlation coefficient is higher than 0.96and the Spearman ran k-order correlation coefficient is higher than 0.95.Compared with the existing evaluation methods,this method is superior to the traditional non-reference evaluation method and can objectively reflect the influence of di fferent distorted images on the application of vascular segmentation.