Vascular image classification processing method, device, equipment and storage medium
A blood vessel image and image processing technology, applied in the field of devices, equipment and storage media, and blood vessel image classification and processing methods, can solve the problems of low blood vessel accuracy, inability to guarantee image quality, and affect the processing effect of deep learning models, etc., to achieve high classification Accuracy, the effect of improving accuracy
Active Publication Date: 2021-08-13
TENCENT TECH (SHENZHEN) CO LTD
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[0004] However, when collecting fundus images, the quality of the collected images cannot be guaranteed in many cases, and low-quality fundus images will affect the processing effect of the deep learning model, resulting in low accuracy in classifying blood vessels in fundus images
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[0078] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.
[0079] Before describing the various embodiments shown in the application, several concepts involved in the application are firstly introduced.
[0080] 1) AI (Artificial Intelligence, artificial intelligence), AI is the use of digital computers or digital computer-controlled machines to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use k...
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The present application relates to a blood vessel image classification processing method, device, equipment and storage medium, and relates to the technical field of artificial intelligence. The method includes: inputting the first blood vessel image sample into the first image processing model to obtain predicted enhanced image and predicted blood vessel position information; based on the second blood vessel image sample, blood vessel position labeling information, predicted enhanced image and predicted blood vessel position information, The first image processing model is trained; while the above scheme is training the blood vessel classification model, the influence of the image quality on the blood vessel classification is also considered, so that the end-to-end blood vessel classification model generated based on the first image processing model after the training can be used for subsequent training. Low-quality vascular images have higher classification accuracy, thereby improving the accuracy of classification of blood vessels in vascular images by artificial intelligence.
Description
technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular to a blood vessel image classification processing method, device, equipment and storage medium. Background technique [0002] In the medical field, quantitative analysis of retinal blood vessels helps to limit the potential risks of various cardiovascular and cerebrovascular diseases, and retinal artery and vein (Artery or Vein, A / V) classification lays the foundation for quantitative analysis of retinal blood vessels. [0003] In related technologies, retinal A / V classification usually processes an input fundus image through a pre-trained end-to-end deep learning model, and directly outputs the positions of arteries and / or veins in the fundus image. Wherein, the above-mentioned deep learning model is usually obtained by taking fundus image samples as input, and using positions of arteries and / or veins in the fundus image samples as labeling information...
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IPC IPC(8): G06K9/62G06T7/70G06T5/50G16H30/20G06N3/08G06N20/00
CPCG06T7/70G06T5/50G16H30/20G06N3/08G06N20/00G06T2207/30101G06T2207/30041G06F18/2431G06F18/214G06V40/193G06V10/82G06V10/26A61B3/1241A61B3/0025G06N3/04G06N3/045Y02T10/40G06V10/70G06T2207/20081
Inventor 余双陈文婷马锴郑冶枫
Owner TENCENT TECH (SHENZHEN) CO LTD