A Method for Evaluating Fundus Image Quality

Abstract

The invention discloses a fundus image quality evaluation method, which considers the influence of blurring, overexposure and underexposure on the segmentation accuracy of the fundus image, extracts statistical feature vectors, texture feature vectors, and shape feature vectors to form feature vectors, and then uses the support Vector regression trains the feature vectors of all distorted fundus images to construct a prediction model; in the test phase, by calculating the feature vectors of the distorted fundus images used for testing, and according to the prediction model constructed in the training phase, the distortion used for testing is predicted The segmentation accuracy value of the fundus image, because the obtained feature vector information can better reflect the change of the distortion of the distorted fundus image on the segmentation accuracy, so the predicted segmentation accuracy value and the real segmentation accuracy value are effectively improved. The correlation between the results, that is, the ability to accurately and automatically evaluate the quality of fundus images, effectively improves the correlation between objective evaluation results and subjective perception.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to a fundus image quality evaluation method. Background technique [0002] The fundus image is captured by a special fundus camera. The fundus image includes the main physiological structures such as the optic disc, macula and blood vessels in the retina, and is an important type of image in medical imaging. Among them, the optic disc appears as a nearly circular bright color area in the normal fundus image, which has the strongest contrast with the background area, and is the initial area of ​​the optic nerve and blood vessels; the macula is rich in lutein, so it is in the normal fundus The image shows a dark area, and the dark area has no blood vessel structure, and there is an inward sunken area called the fovea in the center of the macula; the blood vessels start from the optic disc area and extend to the entire interior of the eyeball, presenting a tree-like distribution th...

AI Technical Summary

Problems solved by technology

[0003] Although the quality evaluation methods of fundus images are becoming more and more mature, most of them still rely on the subjective judgment of medical researchers. Although this subjective judgment method has certain reference value in evaluating the overall quality of fundus images , but it is difficult to evaluate the impact of fundus image quality on segmentation by subjective means

Fundus images can be used to extract blood vessel information, locate the optic disc, locate the macular area, etc. These applications provide huge information for the diagnosis and treatment of ophthalmic diseases, but the fundus images will inevitably be disturbed by noise during the acquisition and transmission process , leading to the loss of effective retinal information collected, which in turn affects the doctor's diagnosis

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