Method and device for location and segmentation of optic disc in eyeground image, and storage medium

Abstract

The present invention provides a method and device for location and segmentation of an optic disc in an eyeground image, and a storage medium. The method comprises in the initial location phase of an optic disc: performing improved weighting graying of a colorful eyeground image; employing the least square method to perform ellipse fitting to estimate the radius of the optic disc; employing multiple morphological operations to eliminate the interference of artery and vein vasculars, employing histogram statistics to determine an adaptive threshold to segment an area of front 0.01% brightness in the eyeground, and taking the geometric center of the area as an estimated optic disc center; and finally determining an optic disc location rectangle frame. In the optic disc accurate location and segmentation phase, the GrabCut method is employed to segment the optic disc, and the segmented area contour employs the ellipse fitting to determine the optic disc position and size parameters so as to complete the location of the optic disc. The condition of too big radius of the optic disc in the GrabCut segmentation result is subjected to secondary segmentation to determine a new threshold and perform contour fitting to obtain a final segmentation result.

Description

technical field [0001] The present application relates to the field of image analysis, in particular to a method, device and storage medium for accurately locating and segmenting the optic disc in a color fundus image. Background technique [0002] Obtaining the optic disc from the fundus image, locating and segmenting the optic disc are the most urgent needs of fundus image measurement. For the location and segmentation of the optic disc, the conventional method is to segment the optic disc by using image processing methods such as image preprocessing, filtering, ellipse fitting and morphology. The above methods have certain effects, but still have certain defects. [0003] For example, Lalonde (Lalonde M, Beaulieu M, Gagnon L. Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching [J]. Medical Imaging, IEEE Transactions on, 2001, 20(11): 1193-1200) etc. Using Hausdorff-based template matching technology combined with pyram...

AI Technical Summary

Problems solved by technology

[0006] The current method is good for its own test data set, but it may not achieve good segmentation results for other data sets, which may be due to the fact that the training parameters are not necessarily suitable for color fundus images of various types and sizes

The segmentation ideas and methods of filtering, morphology, ellipse fitting and graph theory used in these methods have been tested to have obvious effects on segmentation, but they need to be implemented step by step to adapt to various fundus maps

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