Retinal fundus image classification method based on improved CNN model

A picture classification and retina technology, applied in the field of image processing, can solve the problems of unrepresentative single data set, limited classification method, poor picture classification accuracy, etc., and achieve the effect of high reliability, good accuracy and less resource occupation

Active Publication Date: 2020-05-12
HUNAN UNIV
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AI Technical Summary

Problems solved by technology

However, the current classification technology generally uses a small single data set to train and classify the classifier; however, a single data set is not representative, and the classifier uses a relatively primitive classifier, so it makes The classification accuracy of pictures is poor, which limits the application of classification methods

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  • Retinal fundus image classification method based on improved CNN model
  • Retinal fundus image classification method based on improved CNN model
  • Retinal fundus image classification method based on improved CNN model

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Embodiment Construction

[0044] Such as figure 1 Shown is the schematic flow chart of the method of the present invention method: the method for classifying retinal fundus pictures based on the improved CNN model provided by the present invention comprises the following steps:

[0045] S1. Classify and mark the acquired training pictures; specifically, divide the training pictures into abnormal and normal categories, which are represented by disease, disease=1 means abnormal, disease=0 means normal; then mark the abnormal pictures again as abnormal Degree, represented by level, the value of level is 0, 1, 2, 3 and 4, which are used to indicate the lightest abnormality to the heaviest abnormality in turn;

[0046] S2. Perform image preprocessing on the training picture obtained in step S1; specifically, the following steps are used for preprocessing:

[0047] A. Obtain the eyeball radius according to the pixel value of each picture;

[0048] B. Cut out the smallest square picture containing the eyeba...

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Abstract

The invention discloses a retinal fundus image classification method based on an improved CNN model. The method comprises the following steps: classifying and marking acquired training images; performing image preprocessing on the training picture; establishing an improved CNN model; training the improved CNN model by adopting the training pictures to obtain a picture classifier; and classifying the retinal fundus images to be detected by adopting an image classifier to obtain a final classification result. The improved CNN model and the improved CNN classification method based on multiple tasks are excellent in performance, higher in efficiency, less in occupied resources, high in reliability and good in accuracy.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a method for classifying retinal fundus pictures based on an improved CNN model. Background technique [0002] With the development of economy and technology and the improvement of people's living standards, people are paying more and more attention to their own health. [0003] Retinal fundus pictures can reflect people's health status to a certain extent. Therefore, analyzing and classifying the color fundus pictures of the detected person has become an auxiliary detection method for retinopathy (such as diabetic retinopathy). [0004] At present, there have been a large number of studies on the classification of color fundus images of diabetic retinopathy. However, the current classification technology generally uses a smaller single data set to train and classify the classifier; however, a single data set is not representative, and the classifier uses a relativel...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/08
CPCG06N3/084G06V40/197
Inventor 荣辉桂奚子为蒋洪波王敏火生旭
Owner HUNAN UNIV
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