Automatic screening method for diabetic retinopathy based on naive Bayes and support vector machine

Abstract

The invention discloses a diabetic retinopathy automatic screening method based on naive Bayes and a support vector machine, which comprises the following steps: preprocessing an original color fundusimage, and extracting a blood vessel image from the original color fundus image; redrawing the pre-processed image according to the blood vessel image, wherein a blood vessel pixel value in the pre-processed image is determined by non-blood vessel pixels in the surrounding area to obtain a blood vessel redrawn image for reducing the blood vessel contrast; extracting a candidate microaneurysm areafrom the vascular redrawing image, and then extracting features of the candidate microaneurysm; and outputting, by a naive Bayesian classifier, a mark matrix of the microaneurysm according to the candidate microaneurysm features so as to obtain the number of the microaneurysm; and giving, by the support vector machine, a glyconet disease detection result according to the preprocessed image and the number of the microaneurysm. The method can effectively avoid accurate segmentation of the blood vessel and the microaneurysm, the extracted features are simple and easy to operate, and whether a patient suffers from the diabetic retinopathy or not can be automatically detected.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, and relates to an automatic screening method for diabetes mellitus based on naive Bayesian and support vector machine. Background technique [0002] Diabetic retinopathy is one of the common complications of diabetes. It is a retinal microvascular disease, and its full name is diabetic retinopathy. It is estimated that more than 75% of people with diabetes will have some form of diabetes over 20 years. Diabetic reticulosis affects the vision of patients. In the proliferative stage of diabetic reticulum, new blood vessels continue to grow, which may lead to retinal detachment and cause blindness in patients. However, diabetic reticulosis is an eye disease that can prevent blindness. At the same time, the eyes, as an important organ for human beings to perceive the surrounding environment, obtain more than 80% of the information. [0003] In clinical practice, the easiest and mos...

AI Technical Summary

Problems solved by technology

On the one hand, this type of method requires familiarity with the pathological changes of diabetic retinopathy in order to add prior information when extracting differential features to make the learning model more robust, and the extracted features have a high latitude; on the other hand, the detection results are heavily dependent on the structure of the fundus. Segmentation accuracy, but optic disc segmentation is easily affected by lesions, and similar features between lesions and fundus structures interfere with each other

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