Automatic Segmentation Method of Eye Cup in Fundus Image Based on Improved PDE Image Inpainting

Abstract

The invention discloses an eye fundus image optical cup automatic segmentation method based on improved PDE image repairing. The method is carried out with following steps: reading and normalizing an original image; selecting channels for the original image; enhancing the image based on a morphological principle; positioning blood vessels based on an image subtraction; filling and repairing blood vessel areas by the use of an improved BSCB model; performing median filtering and noise reduction for the image and highlighting object areas through gamma transformation; and preliminarily obtaining an optical cup contour through a level set algorithm under a condition that the mass center of the brightest pixel point set on the image serves as an initial seed point. According to the invention, the image in which the blood vessels are filled and repaired eliminate the influence on optical cup segmentation by the blood vessel areas to a certain extent; the accuracy of optical disk segmentation is improved; the seed point is automatically selected as the contour of an optical cup is obtained through the level set algorithm; and manual intervention in a conventional semi-automatic method is reduced.

Description

technical field [0001] The invention belongs to the field of medical image processing, relates to an improved partial differential equation (PDE)-based BSCB image repair model, and realizes the automatic segmentation of the optic cup of the fundus image. Background technique [0002] Fundus and optic nerve tissue lesions caused by various reasons are called fundus optic nerve diseases (such as glaucoma, diabetic retinopathy, etc.), and these diseases all have the risk of blindness. The incidence of such diseases is very high worldwide, and it is showing an upward trend, and the change of the cup size in the fundus image has important guiding significance for the early diagnosis and treatment of glaucoma and other lesions. Segmentation is a key technique for computer-aided diagnosis of eye-related lesions. [0003] At present, there are many researches on the automatic segmentation of the optic cup in fundus images. These methods are generally divided into three types: meth...

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Problems solved by technology

[0004] However, the current methods for automatic segmentation of the optic cup are still very limited. In the process of segmentation of the optic cup, the current method is easily affected by the unclear edge of the optic cup caused by blood vessels, resulting in inaccurate segmentation results. Therefore, the existing The segmentation results of the method are still in the preliminary stage

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