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System and methods for estimation of blood flow characteristics using reduced order model and machine learning

机译:使用减少订单模型和机器学习估计血流特性的系统和方法

摘要

Systems and methods are disclosed for determining blood flow characteristics of a patient. One method includes: receiving, in an electronic storage medium, patient-specific image data of at least a portion of vasculature of the patient having geometric features at one or more points; generating a patient-specific reduced order model from the received image data, the patient-specific reduced order model comprising estimates of impedance values and a simplification of the geometric features at the one or more points of the vasculature of the patient; creating a feature vector comprising the estimates of impedance values and geometric features for each of the one or more points of the patient-specific reduced order model; and determining blood flow characteristics at the one or more points of the patient-specific reduced order model using a machine learning algorithm trained to predict blood flow characteristics based on the created feature vectors at the one or more points.
机译:公开了用于确定患者的血流特征的系统和方法。一种方法包括:在电子存储介质中接收至少一部分患者的患者的特定于患者的患者的特异性图像数据,其几何特征在一个或多个点处;从接收的图像数据产生特定于患者特定的减少阶模型,患者特定的减少阶模型包括阻抗值的估计和患者脉管系统的一个或多个点处的几何特征的简化;创建一个特征向量,包括用于患者特定的减少订单模型的一个或多个点中的每一个或多个点的阻抗值和几何特征的估计;使用培训的机器学习算法确定患者特定的减少阶模型的一个或多个点处的血流特性,以预测基于在一个或多个点处的产生的特征向量来预测血流特性。

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