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Diabetic retinopathy recognition method and device and electronic equipment

A technology for diabetic retinopathy and identification methods, applied in the field of devices and electronic equipment, and identification methods for diabetic retinopathy, which can solve the problems of incomplete identification results and low recognition accuracy of diabetic retinopathy

Inactive Publication Date: 2019-11-22
北京大恒普信医疗技术有限公司
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  • Abstract
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  • Claims
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Problems solved by technology

[0003] In view of this, the purpose of the embodiment of the present application is to provide a diabetic retinopathy recognition method, device and electronic equipment to improve the problems existing in the prior art that the recognition accuracy of diabetic retinopathy is low and the recognition results are incomplete.

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  • Diabetic retinopathy recognition method and device and electronic equipment
  • Diabetic retinopathy recognition method and device and electronic equipment
  • Diabetic retinopathy recognition method and device and electronic equipment

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Embodiment Construction

[0042] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

[0043] Based on the development of deep learning and artificial intelligence in recent years, breakthroughs have been made in image recognition and target detection technology. The deep learning model trained on public data sets has reached or even exceeded the level that humans can achieve in some scenarios. . Image recognition is image classification, which is to identify the main target in the picture, such as identifying whether the picture is a photo of a cat or a photo of a dog; target detection is to identify which objects are contained in the picture and locate them, such as whether there are objects in the picture Cat or dog, where is the location. Image recognition and object detection are the two most widely used fields of artificial intelligence in the field of image processing.

[004...

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Abstract

The invention provides a diabetic retinopathy recognition method and device and electronic equipment, and relates to the technical field of image recognition. The method comprises the following steps:collecting a fundus image to be recognized; inputting the fundus image into a diabetic retinopathy recognition model, wherein the diabetic retinopathy recognition model is obtained by training basedon an instance segmentation model; determining a focus in the fundus image through the diabetic retinopathy recognition model; and labeling at least one of the type, the position and the shape of thefocus through the diabetic retinopathy recognition model. According to the method, the type, the position and the shape of the focus in the fundus image are directly recognized through the diabetic retinopathy recognition model, and accurate recognition of lesion staging can be achieved.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular, to a method, device and electronic equipment for identifying diabetic retinopathy. Background technique [0002] With the rapid development of computer technology and image processing technology, related technologies have been widely used in medicine. For example, in the artificial intelligence-assisted recognition of diabetic retinopathy based on fundus images, image recognition-based technology can also be used Technology based on object detection. The existing artificial intelligence-assisted recognition system for diabetic retinopathy based on image recognition technology has the problem of low recognition accuracy. On the other hand, the existing technical solutions usually can only roughly locate the lesion, but cannot directly display the shape of the lesion, requiring further manual judgment by professionals, and there is a problem of incomplete recognit...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/194
CPCG06T7/0014G06T2207/20081G06T2207/20084G06T2207/30041G06T2207/30096G06T2207/30101G06T7/194
Inventor 金蒙李卫超钟利伟
Owner 北京大恒普信医疗技术有限公司
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