Image processing method and device, computer readable storage medium and electronic equipment

Abstract

The invention provides an image processing method and device, a computer readable storage medium and electronic equipment, and relates to the technical field of image processing. The image processing method comprises the following steps: determining optic disc position information corresponding to a fundus image to be processed based on a preset target detection algorithm; determining an optic disc segmentation image and optic disc boundary information corresponding to the fundus image to be processed based on the optic disc position information and a preset edge detection algorithm; and determining an optic cup segmentation image and optic cup boundary information corresponding to the fundus image to be processed based on the optic disc position information. According to the image processing method provided by the embodiment of the invention, the eye fundus image optic disk and optic cup identification and extraction can be realized, and the segmentation precision reaches a sub-pixel level or above.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to an image processing method and device, a computer-readable storage medium, and electronic equipment. Background technique [0002] Glaucoma is one of the three major blindness diseases in the world, and its irreversibility makes its early diagnosis and treatment play a vital role in improving the quality of life of patients. In the automatic screening of glaucoma, the cup-to-disk ratio is one of the commonly used evaluation indicators. The segmentation method is used to segment the optic cup and optic disc in the fundus image, and then the cup-to-disk ratio is calculated. However, the existing optic cup and optic disc segmentation methods are easily affected by the image quality of the fundus image, such as illumination, occlusion, etc., resulting in a decrease in segmentation accuracy, which in turn leads to a low accuracy of the calculated cup-to-disc ratio. ...

AI Technical Summary

Problems solved by technology

However, the existing optic cup and optic disc segmentation methods are easily affected by the image quality of the fundus image, such as illumination, occlusion, etc., resulting in reduced segmentation accuracy, which in turn leads to low accuracy of the calculated cup-to-disk ratio

In addition, the existing optic disc and cup segmentation is mostly pixel-level precision, and the positioning of the boundary is not accurate enough, which leads to the inaccurate calculation of the cup-to-disc ratio, which affects the auxiliary diagnosis of diseases

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