Deep learning model and device for predicting blood flow features on flood flow vector paths

A technology of deep learning and blood flow, applied in image data processing, instruments, calculations, etc., to achieve the effects of saving medical economic costs, accurate prediction results, and improving prediction accuracy

Active Publication Date: 2018-10-16
HANGZHOU ARTERYFLOW TECH CO LTD
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AI Technical Summary

Problems solved by technology

The deep learning model only takes image features, structural features, and functional features as input, and does not combine the physiological information of the human body and other information related to the living environment. Therefore, compared with the blood flow features obtained by invasive tests, using this There are some differences in the blood flow characteristics obtained by the deep learning model in the patent application

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  • Deep learning model and device for predicting blood flow features on flood flow vector paths
  • Deep learning model and device for predicting blood flow features on flood flow vector paths
  • Deep learning model and device for predicting blood flow features on flood flow vector paths

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[0054] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and do not limit the protection scope of the present invention.

[0055] In the existing method, only the blood flow characteristics on the vector path are obtained, which can include the blood flow characteristics on the centerline of the blood vessel, on the blood vessel wall or other points in the blood, but the number of these points is much smaller than the grid points in CFD The number of available information is much smaller than that of CFD.

[0056] Therefore, the device for predicting the blood flow characteristics on the blood flow vector path provided by the present invention is as follows: figure 1 As shown, the device 10...

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Abstract

The invention discloses a deep learning model for predicting flood flow features on flood flow paths. The deep learning model receives structural features of each point on the blood flow vector paths,physiological features of humans and personal features, and outputs the blood flow features of each point on the blood flow vector paths. The deep learning model comprises a support vector machine; and after the structure features of each point on the blood flow vector paths, the physiological features of humans and the personal features are input to the support vector machine, blood flow features of each point on the blood flow vector paths are obtained through calculation. The deep learning model integrates the structural features of blood vessels, physiological features and personal features of users, so that the blood flow features on the blood flow vector paths can be accurately predicted.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to a deep learning model for predicting blood flow characteristics on a blood flow vector path, and a device for predicting blood flow characteristics on a blood flow vector path. Background technique [0002] Blood flow characteristics have very important guiding significance in medicine. Fraction Flow Reverse (FFR) is a parameter for functional evaluation of coronary artery stenosis, which is defined as: in the case of coronary artery stenosis, the target measurement The ratio of the maximum blood flow that can be obtained by the myocardial region supplied by the blood vessel to the maximum blood flow that the same region can theoretically obtain under normal conditions. This ratio can be calculated from the ratio of the pressure distal to the patient's stenosis to the pressure at the aorta when the vessel is at maximal hyperemia induced by intravenous adenosine....

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T7/0012G06T2207/30104G06T2207/20084G06T2207/20081
Inventor 向建平李炳辉赵行陈少辉冷晓畅
Owner HANGZHOU ARTERYFLOW TECH CO LTD
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