Diabetic retinopathy grading method based on depth map network

A technology of diabetic retinopathy and grading method, which is applied in the field of grading and classification of diabetic retinopathy based on deep graph network, can solve the problems of misdiagnosis and the inability of a single image to fully reflect the patient's disease condition, and achieve a simple, accurate and accurate model structure Comprehensive diagnosis results, fast and convenient effect building

Active Publication Date: 2020-02-25
FUDAN UNIV
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Problems solved by technology

[0005] However, such an automated diagnosis method has certain limitations. Due to external factors such as equipment,

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  • Diabetic retinopathy grading method based on depth map network
  • Diabetic retinopathy grading method based on depth map network
  • Diabetic retinopathy grading method based on depth map network

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Embodiment Construction

[0017] In order to make the technical means, creative features, goals and effects of the present invention easy to understand, the method for grading diabetic retinopathy based on the depth map network of the present invention will be described in detail below in conjunction with the embodiments and accompanying drawings.

[0018]

[0019] The method for grading diabetic retinopathy based on a depth graph network in this embodiment is implemented based on a computer, and the computer includes at least one graphics card for GPU acceleration. The diabetic retinopathy grading model used in the diabetic retinopathy grading method and the image recognition process are stored in the computer in the form of executable code.

[0020] The data set used in this embodiment is obtained by obtaining fundus images taken by primary medical and health institutions in 13 districts of Shanghai, and constitutes an eye map data set including a total of 252,251 fundus maps. In the fundus map dat...

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Abstract

The invention provides a diabetic retinopathy grading method based on a depth map network. The actual diagnosis process of an ophthalmologist on the diabetic retinopathy can be effectively simulated;information transmission and integration of disease characteristics are carried out on a plurality of images of a single eye of a patient to obtain a more accurate diagnosis result. The method is characterized by comprising the following steps of S1, performing preprocessing at least including image quality detection and left and right eye classification and recognition on a plurality of to-be-detected eye fundus images of two eyes of a patient to obtain preprocessed eye fundus images; s2, constructing logic diagram data according to the plurality of preprocessed eye fundus images corresponding to the single eye of the patient, wherein the logic diagram data comprises a full-connection diagram taking the plurality of preprocessed eye fundus images as nodes; and S3, inputting the logic diagram data into a pre-trained diabetic retinopathy grading model so as to obtain diabetic retinopathy grade information of the patient.

Description

technical field [0001] The invention belongs to the fields of computer vision and medical treatment, and relates to a method for classifying diabetic retinopathy, in particular to a method for grading diabetic retinopathy based on a depth map network. Background technique [0002] Diabetic retinopathy (DR) is an eye disease associated with diabetes. About 40% to 45% of people with diabetes suffer from the disease to varying degrees. If diabetic retinopathy is detected in time, vision loss can be slowed or avoided. Based on the fundus images taken by patients, the severity of diabetic retinopathy can be divided into five grades according to the disease characteristics such as lesions, which are normal, mild in the non-proliferative stage, moderate in the non-proliferative stage, severe in the non-proliferative stage, and proliferative stage. [0003] Manual detection of diabetic retinopathy is a time-consuming process with high resource demands. Where diabetes rates are hi...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08G16H30/40G16H50/20
CPCG06N3/084G16H30/40G16H50/20G06V40/193G06V40/197G06N3/045
Inventor 侯君临魏彤杜姗姗冯瑞
Owner FUDAN UNIV
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