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A method for screening fundus images

A fundus image and image type technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as labor-intensive, low efficiency, and accelerated diagnosis of fundus diseases, so as to improve work efficiency, overcome noise errors, and save The effect of valuable time

Inactive Publication Date: 2019-05-28
REDASEN TECH DALIAN CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] Aiming at the above-mentioned problems existing in the prior art, the present invention provides a method for screening fundus images, which can complete the screening and classification of fundus pictures, speed up the diagnosis of fundus diseases, solve the problems of a large amount of labor and low efficiency, and finally provide To improve the health of society as a whole

Method used

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  • A method for screening fundus images
  • A method for screening fundus images
  • A method for screening fundus images

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Embodiment 1

[0040] This embodiment provides a method for screening fundus images, the specific steps are as follows:

[0041] ① Receive the photographed fundus pictures;

[0042] ② Preprocessing and separation of G channel images of 24-bit true color retinal images in RGB format;

[0043] ③ Adaptive histogram equalization is used to optimize the problems of uneven illumination, too concentrated gray scale distribution and low contrast in the image;

[0044] ④ Use the Morlet wavelet formula to segment the image and extract the vascular skeleton;

[0045] ⑤Using multi-scale Gaussian matching filter to optimize the tiny blood vessel part in the image;

[0046] ⑥ Binarization based on the hysteresis threshold method performs binarization processing on the image after Gaussian matching filtering, thereby excluding most of the non-vascular pixels;

[0047] ⑦The G channel image is processed by Gabor wavelet transform. Since its core is a Gaussian function, the gray intensity distribution of t...

Embodiment 2

[0057] This embodiment specifically explains the Morlet wavelet transform, the Gabor wavelet fusion feature vector and the neural network technology for deep learning of image features involved in the first embodiment.

[0058] (1) Morlet wavelet transform method, specifically

[0059]

[0060] Among them, * indicates conjugate; Cω indicates normalization constant; ω indicates wavelet to be analyzed; b is displacement vector; θ is rotation angle; a is scale factor, r is filter; ) reflects the degree of similarity between the gray distribution curve of the image and the wavelet sequence function. When the local frequency of the image is close to the oscillation frequency of the wavelet function of the corresponding scale, the modulus value of Tω(b,θ,a) is relatively large, and along the scale In the axial direction, the line connecting the position of the maximum modulus value of the wavelet transform coefficient is defined as the "ridge" of the wavelet transform, and its ma...

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Abstract

A method for screening fundus images, according to the tree-like network structure and gray distribution characteristics of retinal blood vessels, through the Morlet wavelet and Gaussian matching filter segmentation method, from the multi-scale discrete Gaussian kernel to check the blood vessel skeleton, so as to improve the relationship between tiny blood vessels and the background area At the same time, combined with the Gabor wavelet algorithm, the feature vector composed of its wavelet characteristics and the gray information of the green channel is used; through the deep neural network technology, the eye features such as arteriovenous blood vessels and blood vessel intersections, arch bridges, macula, black spots, and white spots are analyzed. Carry out label learning training; this application can complete the screening and classification of fundus images, speed up the diagnosis of fundus diseases, solve the problems of labor-intensive and low efficiency, and finally strive to improve the health level of the whole society.

Description

technical field [0001] The invention belongs to the field of fundus medical technology, in particular to a method for screening fundus images. Background technique [0002] Fundus disease is an important cause of human blindness, which has seriously threatened people's health and quality of life; high blood pressure, arteriosclerosis, vascular obstruction, diabetes and senile macula and other common and difficult to cure diseases have been favored by society. It is an important issue that urgently needs to be solved in the medical field. [0003] In recent years, it has been clinically confirmed that the occurrence and development of many diseases in the human body will be reflected in the fundus to varying degrees. Therefore, many diseases can be detected at an early stage and diagnosed and treated in advance through the analysis of the characteristics of the fundus, so as to control the further development of the disease. develop. This recognition makes fundus medical tr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/168G06K9/62
CPCG06T7/0012G06T2207/20081G06T2207/20084G06T2207/20064G06T2207/30041G06F18/2411G06F18/214
Inventor 张松涛李德衡薛丹
Owner REDASEN TECH DALIAN CO LTD
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