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Cardiovascular surgery index risk classification method and system based on retina image

A classification method and retinal technology, applied in blood vessel patterns, biological neural network models, instruments, etc., can solve the problems of retinal image feature interference, uneven light, and limit the number of potential participants, etc., to achieve high efficiency and scalability, The effect of improving generalization ability and good interpretability

Pending Publication Date: 2021-06-22
SOUTH CHINA UNIV OF TECH +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Second, relatively new ROP screening techniques also limit the number of potential participants
Third, retinal images are captured by handheld and contact retinal cameras, so the features of retinal images are disturbed by factors such as light exposure, contrast, sensor sensitivity, and illuminance
Poor retinal images greatly reduce usability due to uneven lighting, image blur and low contrast
Fourth, most deep learning-based classification models have no interpretable feedback mechanism for clinicians

Method used

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  • Cardiovascular surgery index risk classification method and system based on retina image
  • Cardiovascular surgery index risk classification method and system based on retina image
  • Cardiovascular surgery index risk classification method and system based on retina image

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Embodiment 1

[0055] In this embodiment, retinal images are used to predict the risk of postoperative complications according to two classifications. The prediction result 1 indicates that the risk of postoperative complications is high, and the prediction result 0 indicates that the risk of postoperative complications is low. figure 1 For a specific logic flow diagram, input an image, convert the retinal RGB image into a grayscale image, and then perform linear normalization and adaptive limit histogram equalization to obtain a contrast-enhanced retinal grayscale image; use the pre-trained The neural network U-net neural network model of U-shaped structure extracts the blood vessels of the enhanced retinal grayscale image to obtain the blood vessel grayscale image; random rotation, translation and other data enhancement are performed on the blood vessel grayscale image; two stages are adopted The trained supervised convolutional neural network model DCRBFNN is used for the classification ta...

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Abstract

The invention discloses a cardiovascular surgery index risk classification method and system based on a retina image, and aims to solve the problems that an actual retina image is not clear and is inconsistent in exposure, and the like. The method comprises the steps: firstly, carrying out the preprocessing of contrast enhancement and blood vessel extraction on the retina image; data enhancement such as random rotation and translation is carried out on the extracted blood vessel map to increase the training amount of the data, so that the generalization ability of the model is improved; a two-stage supervised convolutional neural network model is designed for a classification task of a vascular map, so that not only can the features of retina images be learned, but also the correlation between the retina images is considered; a proper hidden layer node number is selected by adopting a localized generalization error, so that the generalization ability of the model is improved; in addition, the model also has the capability of generating a pixel-level fine-grained pixel-level saliency heat map, and has good interpretability.

Description

technical field [0001] The present invention relates to the technical fields of image processing and image analysis, in particular to a method and system for risk classification of cardiovascular surgery indicators based on retinal images. Background technique [0002] The number of people suffering from complex cardiovascular diseases is increasing every year. The evaluation of surgical indicators in patients with complex coronary heart disease is crucial for selecting the appropriate surgical approach, but there is still a lack of an accurate and interpretable method for preoperative assessment of surgical risk and prognosis. Vascular patterns in retinal images of patients with complex coronary artery disease can reflect cardiovascular severity, so retinal images can be used to predict risk classification for cardiovascular surgery indicators. Surgical index risk classification from retinal images is challenging due to limited retinal image data available to patients and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V40/10G06V40/14G06N3/045G06F18/24G06F18/214
Inventor 吴永贤梁海聪彭庆晟钟灿琨杨小红
Owner SOUTH CHINA UNIV OF TECH
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