公开(公告)号：US20140073976A1

公开(公告)日：2014-03-13

申请号：US13895871

申请日：2013-05-16

申请人： Timothy FONTE ,  Gilwoo CHOI ,  Leo GRADY ,  Michael SINGER

发明人： Timothy FONTE ,  Gilwoo CHOI ,  Leo GRADY ,  Michael SINGER

IPC分类号： A61B5/026

CPC分类号： A61B5/026 ,  A61B5/0022 ,  A61B5/02007 ,  A61B5/0205 ,  A61B5/021 ,  A61B5/024 ,  A61B5/107 ,  A61B5/14535 ,  A61B5/14546 ,  A61B5/7267 ,  A61B5/7278 ,  A61B5/7282 ,  A61B5/742 ,  A61B5/743 ,  A61B6/032 ,  A61B6/463 ,  A61B6/504 ,  A61B6/507 ,  A61B6/5217 ,  A61B6/563 ,  A61B2560/0475 ,  G06N7/005 ,  G06N20/00 ,  G16H50/20

摘要： Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

摘要翻译： 公开了用于确定个体特异性血流特性的系统和方法。 一种方法包括针对个体的血管系统的至少一部分获取多个个体中的每一个个体特异性解剖数据和血流特征; 对所述多个个体中的每一个执行关于所述个体特异性解剖数据和血流特性的机器学习算法; 将所执行的机器学习算法基于每个人的个体特异性解剖数据与血流特征的功能估计相关联; 获取至少部分个体血管系统的个体和个体特异性解剖数据; 并且针对个体个体特异性解剖数据中的至少一个点，使用将个体特异性解剖数据与血流特性的功能估计相关的步骤的关系来确定个体的血流特性。

公开(公告)号：US20140073977A1

公开(公告)日：2014-03-13

申请号：US13895893

申请日：2013-05-16

申请人： Leo GRADY ,  Gilwoo CHOI ,  Michael SINGER

发明人： Leo GRADY ,  Gilwoo CHOI ,  Michael SINGER

IPC分类号： A61B5/00 ,  A61B5/02 ,  A61B5/145 ,  A61B5/026 ,  A61B5/021

CPC分类号： A61B5/7267 ,  A61B5/0022 ,  A61B5/02035 ,  A61B5/021 ,  A61B5/026 ,  A61B5/14535 ,  A61B5/742 ,  G16H50/20 ,  G16H50/50 ,  G16H50/70

摘要： Systems and methods are disclosed for estimating patient-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, a geometric model and estimated blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the geometric model and estimated blood flow characteristics for each of the plurality of individuals; identifying, using the machine learning algorithm, features predictive of blood flow characteristics corresponding to a plurality of points in the geometric models; acquiring, for a patient, a geometric model of at least part of the patient's vascular system; and using the identified features to produce estimates of the patient's blood flow characteristic for each of a plurality of points in the patient's geometric model.

摘要翻译： 公开了用于估计患者特异性血流特征的系统和方法。 一种方法包括为多个个体中的每一个获取个体血管系统的至少一部分的几何模型和估计的血流特性; 对所述多个个体中的每一个执行对所述几何模型的机器学习算法和估计的血流特性; 使用机器学习算法识别预测与几何模型中的多个点相对应的血流特性的特征; 为患者获取至少部分患者血管系统的几何模型; 以及使用所识别的特征来产生对患者几何模型中的多个点中的每一个点的患者血流特性的估计。

公开(公告)号：US20140249784A1

公开(公告)日：2014-09-04

申请号：US13864996

申请日：2013-04-17

申请人： Sethuraman SANKARAN ,  Leo GRADY ,  Charles A. TAYLOR

发明人： Sethuraman SANKARAN ,  Leo GRADY ,  Charles A. TAYLOR

IPC分类号： G06F19/00

CPC分类号： G16H50/50 ,  A61B5/02007 ,  A61B5/02028 ,  A61B5/021 ,  A61B5/026 ,  A61B5/055 ,  A61B5/7278 ,  A61B6/032 ,  A61B6/504 ,  A61B6/5217 ,  G06F19/00 ,  G06T7/0012 ,  G06T2207/10081 ,  G06T2207/30104

摘要： Embodiments include systems and methods for determining cardiovascular information for a patient. A method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of the patient's vasculature based on the patient-specific data; and creating a computational model of a blood flow characteristic based on the anatomic model. The method also includes identifying one or more of an uncertain parameter, an uncertain clinical variable, and an uncertain geometry; modifying a probability model based on one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry; determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature; and calculating, based on the probability model and the determined blood flow characteristic, a sensitivity of the determined fractional flow reserve to one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry.

摘要翻译： 实施例包括用于确定患者的心血管信息的系统和方法。 一种方法包括接收关于患者脉管系统的几何形状的患者特定数据; 基于患者特定的数据创建代表患者脉管系统的至少一部分的解剖模型; 并基于解剖模型创建血流特征的计算模型。 该方法还包括识别不确定参数，不确定临床变量和不确定几何中的一个或多个; 基于所识别的不确定参数，不确定临床变量或不确定几何中的一个或多个修改概率模型; 基于解剖模型和患者脉管系统的血流特性的计算模型确定患者血管系统内的血流特性; 并且基于所述概率模型和确定的血液流动特性，将所确定的分数流量储备的灵敏度计算到所识别的不确定参数，不确定的临床变量或不确定几何中的一个或多个。