Choroid layer segmentation method based on ARU-Net

A choroid and layer boundary technology, applied in the field of image processing, can solve time-consuming and subjective problems, and achieve the effect of improving work efficiency

Pending Publication Date: 2021-04-27
FOSHAN UNIVERSITY
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Problems solved by technology

[0003] Based on this, in order to solve the time-consuming and subjective problem of manual image segmentation and analysis of large data sets of optical coherence tomography images by human experts in the prior art, the present invention provides a choroid layer segmentation method based on ARU-Net , its specific technical scheme is as follows:

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Embodiment Construction

[0040] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with its embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and do not limit the protection scope of the present invention.

[0041] It should be noted that when an element is referred to as being “fixed” to another element, it can be directly on the other element or there can also be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and similar expressions are used herein for purposes of illustration only and are not intended to represent the only embodiments.

[0042] Unless otherwise defined, all technical and scientific t...

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Abstract

The invention provides a choroid layer segmentation method based on ARU-Net. The method comprises the following steps: collecting an OCT choroid image; processing the OCT choroid image to obtain a choroid data set; dividing the choroid data set into a training set, a verification set and a test set, and performing data enhancement on the training set; constructing an ARU-Net model, and training the ARU-Net model by using the training set and the verification set; predicting the test set by using the trained ARU-Net model to obtain a choroidal prediction probability graph; setting a probability threshold, and obtaining a choroid segmentation prediction graph; and obtaining a choroidal layer boundary according to the choroidal segmentation prediction graph. According to the invention, the OCT choroidal image can be automatically segmented to obtain the choroidal layer boundary.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a choroid layer segmentation method based on ARU-Net. Background technique [0002] The choroid is an important vascular layer, its main function is to provide oxygen and nutrients for the whole eyeball, and it has the function of light isolation to make the reflected objects clearer. Changes in the choroid are critical for both clinical and research tasks. In particular, for comparison with age-matched data or previously measured patient data, for disease detection and management, it is often necessary to segment the choroidal layer and subsequently measure layer thickness and volume, recording normal aging changes in the eye. In recent years, the introduction of optical coherence tomography (OCT) has allowed non-invasive, high-resolution images of the retina and choroid to be captured for this analysis. However, the prior art involves manual image segmentatio...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/13G06T5/00G06K9/32G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T7/13G06T5/002G06N3/084G06T2207/10101G06T2207/20032G06T2207/20104G06T2207/20081G06T2207/20084G06T2207/30101G06V10/25G06N3/048G06N3/045G06F18/213G06F18/214
Inventor 王雪花许祥丛曾亚光韩定安林静怡覃楚渝刘明迪翁祥涛郭学东王陆权
Owner FOSHAN UNIVERSITY
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