Eye fundus image no-reference quality evaluation method

Abstract

The invention discloses an eye fundus image no-reference quality evaluation method. The method comprises two processes including a training stage and a test stage. The influence of brightness, naturalness and structure layout on eye fundus image quality is considered. A dark channel proportion feature, a bright channel proportion feature, a non-uniform brightness feature, a naturalness quality evaluation score and a structure layout index are extracted to form eigenvectors; and then the eigenvectors of all eye fundus images in a training image set are trained by utilizing support vector regression, and a quality prediction model is built. In the test stage, the eigenvectors of the eye fundus images used for test are calculated, and according to the quality prediction model built in the training stage, prediction is performed to obtain quality objective evaluation prediction values of the eye fundus images. The obtained eigenvector information can better reflect the quality change conditions of the eye fundus images, so that the correlation between objective evaluation results and subjective perception is effectively improved.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to a no-reference quality evaluation method for fundus images. 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. It 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 the most prominent in the fundus image. It appears as a dark area, and there is no blood vessel structure in this area, 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,...

AI Technical Summary

Problems solved by technology

However, during the imaging process, there are often problems such as brighter lighting, darker lighting, uneven lighting, blurring, low contrast, and unreasonable layout, which lead to the acquisition of fundus images that cannot be used for diagnosis and need to be re-shot, which greatly reduces efficiency and increase the cost of medical diagnosis

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