Eye fundus image recognition method and device, equipment, storage medium and program product

A fundus image and recognition method technology, applied in the computer field, can solve problems such as time-consuming and labor-intensive, shortage of ophthalmologists

Pending Publication Date: 2021-06-01
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, it is very time-consuming and labor-intensive to completely rely on docto

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  • Eye fundus image recognition method and device, equipment, storage medium and program product
  • Eye fundus image recognition method and device, equipment, storage medium and program product
  • Eye fundus image recognition method and device, equipment, storage medium and program product

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Embodiment Construction

[0022] Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0023] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0024] figure 1 A flow 100 of an embodiment of the fundus image recognitio...

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Abstract

The invention discloses an eye fundus image recognition method and device, equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence such as computer vision, deep learning and intelligent medical treatment. A specific embodiment of the method comprises the following steps: acquiring a position of a fundus focus, a position of a macular fovea center, a lesion level of a retina and a lesion probability value of a macular region in a fundus image; establishing the correlation between each feature and the lesion type of the macular region based on the position of the fundus focus, the position of the fovea center of the macular, the lesion level of the retina and the lesion probability value of the macular region; performing feature screening based on the correlation between each feature and the lesion type of the macular region; and inputting the screened features into a pre-trained macular region classification decision tree to obtain the category of the macular region. According to the embodiment, computer-assisted eye fundus image recognition is utilized, so that the labor cost is greatly reduced.

Description

technical field [0001] This application relates to the field of computer technology, specifically to the field of artificial intelligence technology such as computer vision, deep learning, and smart medical care, and in particular to fundus image recognition methods, devices, equipment, storage media, and program products. Background technique [0002] Diabetic Retinopathy (DR) refers to the damage of the retinal blood vessel wall caused by diabetes, resulting in the appearance of microvascular tumors, hard exudates and hemorrhages on the retina, resulting in the decline of visual function. It is one of the main blinding diseases. Diabetic macular edema (DME) is a common cause of visual impairment in diabetic patients. Thick or hard exudate deposits. [0003] Currently, automatic classification of DME is performed based on fundus images by locating the fovea and marking the macular area according to the Early Therapeutic Diabetic Retinopathy Research Grading Scale, and usin...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06K9/62G06T7/00G06T7/136G06N3/04G06N3/08
CPCG06T7/0012G06T7/136G06N3/08G06T2207/20081G06T2207/20084G06T2207/30041G06V10/25G06N3/045G06F18/2415G06F18/24323
Inventor 刘佳杨叶辉武秉泓王兆玮王磊李乾
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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