Image feature based eyeground image registering method

Abstract

The invention provides an image feature based eyeground image registering method. The method comprises that a retina eyeground image is obtained and processed to form a binary image; binary images of an image to be registered and a reference image are searched to obtain a binary tree based blood vessel registering point set, a ternary tree based blood vessel registering point set or a binary and ternary tree based mixed blood vessel registering point set; vectors corresponding to all the obtained blood vessel registering point sets are calculated; similarity measuring degrees between all the vectors corresponding to the blood vessel registering point sets in the binary images of the image to be registered and the vectors corresponding to the blood vessel registering point set in the binary image of the reference image; the similarity measuring degrees are ordered, and according to the minimal similarity measuring degree, an optimal registering point set pair of the binary image of the image to be registered and the binary image of the reference image is obtained; and according to node coordinates in the optimal registering point set pair, image registering is carried out on the basis of affine transformation.

Description

technical field [0001] The invention relates to the field of medical digital image processing, and in particular to a fundus image registration method based on image features. Background technique [0002] At present, medical fundus imaging has been widely used to record and examine the clinical manifestations of various retinal diseases, and fundus image registration is also a basic problem in fundus image processing and analysis, the purpose of which is to spatially align two or more images Fundus images at different times, different fields of view or different modalities. At the same time, fundus image registration technology has been widely used in assisting ophthalmology diagnosis and treatment. It can be said that fundus image registration has important clinical application value, and can be used to align various fundus images obtained by the same or different imaging methods to detect retinopathy, such as diabetes, glaucoma, macular degeneration, etc. At the same ti...

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Problems solved by technology

However, the applicant found in the research that Li Chen and Shen Ben only searched for registration points in the form of binary trees when determining the search registration points, while ignoring the diversification of vascular structure intersections in fundus images, and some registration points may also be triple trees. Form, or a mixed form of binary tree and ternary tree, therefore, to a certain extent, many registration point sets are missed, thereby reducing the registration accuracy

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