Choroidal vessel extraction method based on sd‑oct retinal images

Abstract

The invention discloses a choroid membrane blood vessel extraction method based on an SD-OCT retina image, and belongs to the technical field of image processing. The method comprises the following steps: firstly performing Bruch's membrane partitioning on the input SD-OCT image, then carrying out smoothing by adopting bilateral filter, finding pixel points of which the grey scale values are monotonically decreased from top to bottom in each column in a regional image below the smoothed BM, fitting the monotonically decreased pixel points by cubic interpolation values based on a triangle to obtain a binary difference image which is positioned between a fitting surface of the region below the BM region and an original image, and finally removing a small-area communicating region in a binary result to obtain a blood vessel region of a choroid membrane layer. An experiment result shows that large blood vessels of the choroid membrane layer can be better extracted, and the choroid membrane blood vessel extraction method has great significance for facilitating the subsequent retinal disease analysis and improving the working efficiency of a doctor.

Description

technical field [0001] The invention relates to a method for extracting a target area, in particular to a method for extracting choroidal blood vessels based on a frequency-domain optical coherence tomography (SD-OCT) retinal image. Background technique [0002] SD-OCT retinal image is a frequency-domain optical coherence tomography image, which can effectively present changes in the grayscale and structure of retinal tissue layers. Clinical experiments have shown that SD-OCT images can also be used to image choroidal blood vessels. The choroid layer is composed of a large number of blood vessels, which provide nutrition for the retinal layer and is closely related to retinal diseases. Because the choroidal vessels are not obvious on the SD-OCT image, it is difficult for the traditional target extraction method to effectively identify the choroidal vessel area. At present, there is only one document in the world that introduces a choroidal vessel extraction based on SD-OCT i...

AI Technical Summary

Problems solved by technology

Because the choroidal vessels are not obvious on the SD-OCT image, it is difficult for the traditional target extraction method to effectively identify the choroidal vessel area. At present, there is only one document in the world that introduces a choroidal vessel extraction based on SD-OCT images. Method: The multi-scale Hessian matrix analysis method was used to obtain the structure tensor of each small cube of the choroidal layer, and then the choroidal vessels were extracted by the eigenvalues ​​of the structure tensor

This method is difficult to implement and has high complexity

[0003] Therefore, the practicability of the existing choroidal blood vessel extraction method is not high, and it is difficult to meet the needs of clinical ophthalmic disease diagnosis

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