Fundus image recognition method, device and equipment and storage medium

Abstract

The invention relates to the technical field of artificial intelligence, and provides a fundus image recognition method and device, fundus image recognition equipment and a storage medium. The methodcomprises: obtaining an fundus image; extracting first target data from the fundus image, and performing redundancy elimination processing on the first target data to obtain a first central concave feature; generating a macular area mask according to the first central concave feature; intercepting a macular area in the fundus image through a macular area mask to obtain a macular area image; and identifying senile macular degeneration lesion features in the macular area image, and classifying the macular area image according to the senile macular degeneration lesion features. The macular area image is cut from the fundus image through the mask generation model, the macular area image is classified according to AMD focus features in the macular area image, feature data in the macular area image is obvious and easy to recognize, and therefore the classification accuracy of the fundus image is effectively improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to fundus image recognition methods, devices, equipment and storage media. Background technique [0002] Age-related macular degeneration, also known as age-related macular degeneration (Age-related Macular Degeneration, AMD), is one of the leading causes of blindness in adults over 50 years old. In fundus images, AMD lesions often appear as drusen in the macular area and abnormal pigmentation of the retina (such as hyperpigmentation or hypopigmentation). [0003] Currently, only a few machine learning algorithms are used to identify image features to detect AMD. The commonly used method is to use mirror examination, which is a technology used to capture fundus images and analyze different types of skin problems through these images. Fundus imaging technology can improve the accuracy in the diagnosis of age-related macular degeneration. It uses optical magnification te...

AI Technical Summary

Problems solved by technology

[0005] The main purpose of this application is to solve the technical problems of high labor cost and low efficiency of the existing AMD diagnosis method, and propose a fundus image recognition method, which combines deep learning with fundus image recognition, and detects the original fundus through the image quality recognition model Image quality, in order to obtain a fundus image that is easy to identify; the macular area image is cut out from the fundus image through a mask generation model, and the macular area image is classified according to the AMD lesion features in the macular area image, and the features in the macular area image The data is obvious and easy to identify, thus effectively improving the accuracy of fundus image classification

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