Segmentation method and device for blood vessels in fundus image, and storage medium

Abstract

The invention provides a segmentation method and device for blood vessels in a fundus image, and a storage medium. The method comprises the steps that blood vessel segmentation based on Hessian matrixenhancement is conducted, and a threshold value is adopted for segmentation of the blood vessels; a multi-directional linear structure element is used for open operation processing on a G channel, morphological reconstruction is conducted for further enhancement, the multi-directional open operation is adopted and the minimum response is taken to obtain a background without a linear structure, and two images are subtracted to obtain a main vascular network; secondly, multi-directional Gaussian smoothing filtering and multi-directional Gaussian-Laplace filtering are conducted successively, andmulti-directional morphology and morphological reconstruction are adopted to enhance and preserve the filtered vascular network; finally an adaptive threshold value is determined to segment the bloodvessels; the segmentation results of the above two stages are combined to merge and make the final repair to obtain a final blood vessel binary image. The blood vessel segmentation method can improvethe sensitivity of blood vessel recognition and has better calculation efficiency without the need to train in advance.

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 segmenting blood vessels in color fundus images. Background technique [0002] Obtaining blood vessels from fundus images, locating and segmenting blood vessels is the most urgent requirement for fundus image measurement. For the segmentation of blood vessels in the prior art, the conventional method is to segment blood vessels by using image processing methods such as image preprocessing, filtering, fitting, and morphology. The above-mentioned methods have certain effects, but still have certain defects. [0003] For example, multi-scale filtering has a better enhancement effect on blood vessels. Kovács (Kovács G, Hajdu A.Aself-calibrating approach for the segmentation of retinal vessels by templatematching and contour reconstruction[J].Medical image analysis,2016,29:24-46) etc. use matched filtering and contour reconstr...

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Problems solved by technology

[0006] However, the accuracy of the above method is not high. Although some schemes have high accuracy, the amount of calculation is too large and the processing time is long.

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