Abnormality recognition method and device based on eye fundus image, equipment and storage medium

A fundus image and abnormal recognition technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problems of inability to obtain results immediately, high cost, and need for inspection, and achieve simple operation, low cost, and accurate classification Effect

Pending Publication Date: 2019-09-06
PING AN TECH (SHENZHEN) CO LTD
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The method is expensive and requires the tester's D

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  • Abnormality recognition method and device based on eye fundus image, equipment and storage medium
  • Abnormality recognition method and device based on eye fundus image, equipment and storage medium
  • Abnormality recognition method and device based on eye fundus image, equipment and storage medium

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[0055] In order to facilitate the understanding of the present application, the present application will be described more fully below with reference to the relevant drawings. Preferred embodiments of the application are shown in the accompanying drawings. However, the present application can be embodied in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the application more thorough and comprehensive.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used herein in the description of the application are only for the purpose of describing specific embodiments, and are not intended to limit the application.

[0057] An embodiment of the present application provides a metho...

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Abstract

The invention belongs to the technical field of detection, and discloses an abnormality recognition method and device based on an eye fundus image, equipment and a storage medium. The method comprisesthe steps of obtaining an eye fundus image; inputting the eye fundus image into a pre-trained binary classification model, and obtaining a judgment result of whether the eye fundus image output by the binary classification model in response to the eye fundus image is a highly myopia eye fundus image or not; inputting the fundus image which is confirmed to be highly myopia into a pre-trained abnormity detection model, obtaining an recognition result which is output by the abnormity detection model in response to the highly myopia fundus image, wherein the recognition result comprises abnormityor no abnormity in the highly myopia fundus image; and outputting a detection conclusion based on the recognition result. According to the method, high myopia and non-high myopia can be classified more accurately; and fundus abnormality detection is carried out on the classified high myopia image through the trained abnormality detection model, and the detection result serves as an intermediate result of eye fundus diagnosis and can be applied to clinical analysis.

Description

technical field [0001] The present application belongs to the technical field of image detection, and relates to an abnormal recognition method, device, equipment and storage medium based on fundus images. Background technique [0002] Myopia means that in a relaxed state, parallel rays of light pass through the refractive system of the eye and focus in front of the retina, and cannot be clearly imaged on the retina. A myopic eye with a diopter of -6D (D refers to diopters) or more is considered high myopia. According to the survey and statistics of the World Health Organization, the myopia incidence rate of my country's population will be as high as 50% by 2020, and wherein the high myopia population will be as high as 70 million. The formation causes of myopia are more complicated, and there are congenital genetic causes and acquired environmental factors. If one of both parents is highly myopic, the hereditary rate of the child is 56%, and if both parents are highly myo...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T7/00
CPCG06T7/0012G06T2207/10101G06T2207/20081G06T2207/30041G06V40/197G06V40/193
Inventor 王关政王立龙
Owner PING AN TECH (SHENZHEN) CO LTD
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