Lesion detection method and device based on fundus image, equipment and storage medium

A fundus image and detection method technology, applied in the field of image recognition and digital medical treatment, can solve the problem of low accuracy of recognition

Pending Publication Date: 2022-05-13
PING AN TECH (SHENZHEN) CO LTD
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0003] The main purpose of this application is to provide a lesion detection method, device, computer equipment and storag...

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  • Lesion detection method and device based on fundus image, equipment and storage medium
  • Lesion detection method and device based on fundus image, equipment and storage medium
  • Lesion detection method and device based on fundus image, equipment and storage medium

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Embodiment Construction

[0047] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0048] In this embodiment of the present application, data related to medical diagnosis can be acquired and processed based on an artificial intelligence deep learning model. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. .

[0049] refer to figure 1 The embodiment of the present application provides a method fo...

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Abstract

The invention relates to the field of image recognition and digital medical treatment, and discloses an eye fundus image-based lesion detection method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining an eye fundus screening image which comprises a scanning image and a contrast image; inputting the scanned image into a first network in a dual-channel network of a deep learning network model, and obtaining a first image feature obtained by the first network; the first image feature comprises fundus curvature and reflectivity; inputting the contrast image into a second network in a dual-channel network of a deep learning network model, and obtaining a second image feature obtained by the second network; the second image feature comprises blood vessel density and fundus tissue thickness; fusing the first image feature and the second image feature to obtain a fused feature; and matching a maculopathy grade corresponding to the image according to the fusion feature. According to the invention, the accuracy of fundus macular degeneration grade identification can be improved.

Description

technical field [0001] The present application relates to the fields of image recognition and digital medical care, in particular to a fundus image-based lesion detection method, device, computer equipment and storage medium. Background technique [0002] Age-related macular degeneration (AMD) is an eye disease that seriously affects the vision of the elderly. Currently, AMD is detected through in-depth and time-consuming analysis of fundus images based on color fundus photographs. The fundus images used in the current research are fundus color images and optical coherence tomography (OCT) images respectively. The fundus features of the two images are independent of each other, and the degree of fundus macular degeneration cannot be accurately identified. Contents of the invention [0003] The main purpose of this application is to provide a lesion detection method, device, computer equipment and storage medium based on fundus images, aiming to solve the problem of low acc...

Claims

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Application Information

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IPC IPC(8): G06V10/46G06V10/80G06V10/764G06V10/82G06K9/62G06T7/00G06N3/04G16H30/20
CPCG06T7/0012G06N3/04G16H30/20G06T2207/10101G06T2207/20084G06T2207/30041G06T2207/10024G06F18/241G06F18/253
Inventor 郑喜民王天誉舒畅陈又新
Owner PING AN TECH (SHENZHEN) CO LTD
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