Eye fundus image optic cup and optic disc segmentation method under unified framework

A fundus image and optic disc technology, applied in the field of image segmentation, can solve problems such as blurred boundaries, interference, and ignoring edge features, and achieve the effect of enhancing feature expression and weakening differences

Pending Publication Date: 2021-12-31
BEIJING UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

First of all, there are a large number of vascular structures in the optic disc area in the fundus image, which is likely to cause interference during the segmentation process and affect the segmentation accuracy of the optic cup and optic disc.
The second difficulty is that the boundary between the optic disc and the optic cup is very blurred in the fundus image, which is not conducive to the positioning of the optic cup and optic disc, and may ea

Method used

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  • Eye fundus image optic cup and optic disc segmentation method under unified framework
  • Eye fundus image optic cup and optic disc segmentation method under unified framework
  • Eye fundus image optic cup and optic disc segmentation method under unified framework

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Embodiment 1

[0057] The purpose of Embodiment 1 is to provide a method for segmenting the optic cup and optic disc of fundus images under a unified framework.

[0058] The flow chart of the implementation is as figure 1 shown, including the following steps:

[0059] Step S10, obtaining a fundus image data set;

[0060] Step S20, constructing a segmentation network;

[0061] Step S30, training the segmentation model;

[0062] Step S40, dividing the optic cup and optic disc;

[0063] The step S10 of establishing the enhanced image database of the embodiment also includes the following steps:

[0064] In step S100, fundus images of patients with glaucoma and healthy people are acquired with a fundus color camera, as shown in FIG. 2(a).

[0065] Step S101, perform preprocessing and image enhancement on the collected fundus image, including cutting the fundus image to a size of 800×800 pixels with the optic cup as the center, and performing random rotations of 90 degrees, 180 degrees and 2...

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Abstract

The invention discloses an eye fundus image optic cup and optic disk segmentation method under a unified framework, and the method comprises the steps: obtaining an eye fundus image before segmentation, and carrying out the image preprocessing operation, such as cutting and rotating; generating a corresponding mask image according to an optic cup and optic disk area marked on the fundus color photo by an ophthalmologist; constructing a deep network for segmenting an optic cup and an optic disk; iteratively training the deep segmentation network by using the mask image and the fundus image, and optimizing network parameters; and segmenting the optic cup and the optic disc, and obtaining the segmentation results of the optic cup and the optic disc by using the trained segmentation network model. The invention provides a deep neural network for optic cup and optic disc segmentation. The deep neural network comprises a multi-scale feature extractor, a multi-scale feature transition and an attention pyramid structure. According to the method, the optic cup and the optic disc can be effectively segmented, the segmentation precision is high, and meanwhile, a new thought is provided for segmentation of fundus images and segmentation of other medical images.

Description

technical field [0001] The invention belongs to the technical field of image segmentation, and in particular relates to a fundus image optic cup and optic disc segmentation method under a unified framework. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] Medical image segmentation is a basic task in medical image processing and a hotspot in medical image processing at present. Accurate segmentation results are of great significance in clinical diagnosis and disease treatment. Medical image segmentation is to extract the lesions or organs and tissues in the image from the background. [0004] Glaucoma is one of the three leading causes of blindness in the world, and its damage to the vision of patients is irreversible. Therefore, early screening is essential for the prevention and treatment of glaucoma. Currently, fundus color images and...

Claims

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Application Information

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IPC IPC(8): G06T7/10G06T7/00G06K9/46G06K9/62G06N3/04G06N3/08G16H30/20
CPCG06T7/10G06T7/0014G06N3/08G16H30/20G06T2207/30041G06T2207/20016G06N3/045G06F18/253
Inventor 孙光民张忠祥李煜郑鲲朱美龙杨静飞
Owner BEIJING UNIV OF TECH
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