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    SYSTEM AND METHODS FOR INTEGRATED AND PREDICTIVE ANALYSIS OF MOLECULAR, IMAGING, AND CLINICAL DATA FOR PATIENT-SPECIFIC MANAGEMENT OF DISEASES
    1.
    发明申请
    SYSTEM AND METHODS FOR INTEGRATED AND PREDICTIVE ANALYSIS OF MOLECULAR, IMAGING, AND CLINICAL DATA FOR PATIENT-SPECIFIC MANAGEMENT OF DISEASES 审中-公开
    用于疾病特异性管理的分子，成像和临床数据的综合和预测分析的系统和方法

    公开(公告)号：WO2014008332A2

    公开(公告)日：2014-01-09

    申请号：PCT/US2013049205

    申请日：2013-07-03

    Applicant: SIEMENS CORP ,  SIEMENS AG OESTERREICH ,  SIEMENS AG ,  MANSI TOMMASO ,  LIM WEI KEAT ,  KING VANESSA ,  KREMER ANDREAS ,  GEORGESCU BOGDAN ,  ZHENG XUDONG ,  KAMEN ALI ,  KELLER ANDREAS ,  STAEHLER CORD FRIEDRICH ,  WIRSZ EMIL ,  COMANICIU DORIN

    Inventor： MANSI TOMMASO ,  LIM WEI KEAT ,  KING VANESSA ,  KREMER ANDREAS ,  GEORGESCU BOGDAN ,  ZHENG XUDONG ,  KAMEN ALI ,  KELLER ANDREAS ,  STAEHLER CORD FRIEDRICH ,  WIRSZ EMIL ,  COMANICIU DORIN

    IPC: G06F19/00

    CPC classification number: G06F19/3437 ,  G06F19/12 ,  G16H50/50

    Abstract: A system operating in a plurality of modes to provide an integrated analysis of molecular data, imaging data, and clinical data associated with a patient includes a multi-scale model, a molecular model, and a linking component. The multi-scale model is configured to generate one or more estimated multi-scale parameters based on the clinical data and the imaging data when the system operates in a first mode, and generate a model of organ functionality based on one or more inferred multi-scale parameters when the system operates in a second mode. The molecular model is configured to generate one or more first molecular findings based on a molecular network analysis of the molecular data, wherein the molecular model is constrained by the estimated parameters when the system operates in the first mode. The linking component, which is operably coupled to the multi-scale model and the molecular model, is configured to transfer the estimated multi-scale parameters from the multi-scale model to the molecular model when the system operates in the first mode, and generate, using a machine learning process, the inferred multi-scale parameters based on the molecular findings when the system operates in the second mode.

    Abstract translation: 以多种模式操作以提供与患者相关联的分子数据，成像数据和临床数据的综合分析的系统包括多尺度模型，分子模型和连接部件。 多尺度模型被配置为当系统以第一模式操作时，基于临床数据和成像数据生成一个或多个估计的多尺度参数，并且基于一个或多个推断的多尺度模型生成器官功能模型， 系统在第二模式下运行时的缩放参数。 分子模型被配置为基于分子数据的分子网络分析产生一个或多个第一分子发现，其中当系统以第一模式操作时，分子模型受到估计参数约束。 可操作地耦合到多尺度模型和分子模型的连接部件被配置为当系统在第一模式下操作时将估计的多尺度参数从多尺度模型传递到分子模型，并且生成 ，使用机器学习过程，当系统在第二模式下操作时，基于分子发现的推断的多尺度参数。

    ROBOTIC NAVIGATED NUCLEAR PROBE IMAGING
    3.
    发明申请
    ROBOTIC NAVIGATED NUCLEAR PROBE IMAGING 审中-公开
    机动航海导弹探测成像

    公开(公告)号：WO2012064917A1

    公开(公告)日：2012-05-18

    申请号：PCT/US2011/060091

    申请日：2011-11-10

    Applicant: SIEMENS CORPORATION ,  PALADINI, Gianluca ,  KAMEN, Ali ,  KUTTER, Oliver

    Inventor： PALADINI, Gianluca ,  KAMEN, Ali ,  KUTTER, Oliver

    IPC: A61B6/00 ,  A61B5/00 ,  A61B17/34 ,  G01T1/166 ,  G01T1/29 ,  A61B19/00

    CPC classification number: A61B6/4458 ,  A61B5/0064 ,  A61B6/037 ,  A61B6/4057 ,  A61B6/4258 ,  A61B6/4417 ,  A61B6/4464 ,  A61B6/466 ,  A61B6/481 ,  A61B6/5223 ,  A61B6/5229 ,  A61B6/5247 ,  A61B34/30

    Abstract: Robotic navigation is provided for nuclear probe imaging. Using a three-dimensional scanner (19), the surface of a patient is determined (42). A calibrated robotic system positions (48) a nuclear probe about the patient based on the surface. The positioning (48) may be without contacting the patient and the surface may be used in reconstruction to account for spacing of the probe from the patient. By using the robotic system for positioning (48), the speed, resolution and/or quality of the reconstructed image may be predetermined, user settable, and/or improved compared to manual scanning. The reconstruction (52) may be more computationally efficient by providing for regular spacing of radiation detection locations within the volume

    Abstract translation: 提供机器人导航用于核探针成像。 使用三维扫描器（19），确定患者的表面（42）。 校准的机器人系统基于表面定位（48）关于患者的核探针。 定位（48）可以不与患者接触，并且可以在重建中使用表面以考虑探针与患者的间隔。 通过使用用于定位的机器人系统（48），与手动扫描相比，重建图像的速度，分辨率和/或质量可以是预定的，用户可设置的和/或改进的。 通过提供体积内的辐射检测位置的规则间隔，重建（52）可以更有计算效率

    HIERARCHICAL ATLAS-BASED SEGMENTATION
    4.
    发明申请
    HIERARCHICAL ATLAS-BASED SEGMENTATION 审中-公开
    基于分层的基于ATLAS的分类

    公开(公告)号：WO2011109710A1

    公开(公告)日：2011-09-09

    申请号：PCT/US2011/027189

    申请日：2011-03-04

    Applicant: SIEMENS CORPORATION ,  SIEMENS AKTIENGESELLSCHAFT ,  SUNDAR, Hari ,  KAMEN, Ali ,  THOMAS, Boettger

    Inventor： SUNDAR, Hari ,  KAMEN, Ali ,  THOMAS, Boettger

    IPC: G06T7/00

    CPC classification number: G06T7/0024 ,  G06T7/11 ,  G06T7/149 ,  G06T7/30 ,  G06T2207/10081 ,  G06T2207/20016 ,  G06T2207/20128 ,  G06T2207/30016

    Abstract: A method for segmenting an image includes registering an annotated template image to an acquired reference image using only rigid transformations to define a transformation function relating the annotated template image to the acquired reference image (S101). The defined transformation function is refined by registering the annotated template image to the acquired reference image using only affine transformations (S102). The refined transformation function is further refined by registering the annotated template image to the acquired reference image using only multi-affine transformations (S103). The twice refined transformation function is further refined by registering the annotated template image to the acquired reference image using deformation transformations (S104).

    Abstract translation: 用于分割图像的方法包括使用刚性变换将注释的模板图像注册到所获取的参考图像，以定义将所注释的模板图像与所获取的参考图像相关联的变换功能（S101）。 通过使用仿射变换将注释的模板图像注册到所获取的参考图像来改进所定义的变换函数（S102）。 通过仅使用多仿射变换将注释的模板图像注册到所获取的参考图像，进一步改进了精细变换功能（S103）。 通过使用变形变换将所注释的模板图像注册到获取的参考图像来进一步改进两次精化转换函数（S104）。

    METHOD TO IDENTIFY OPTIMUM CORONARY ARTERY DISEASE TREATMENT
    5.
    发明申请
    METHOD TO IDENTIFY OPTIMUM CORONARY ARTERY DISEASE TREATMENT 审中-公开
    识别最佳冠状动脉疾病治疗的方法

    公开(公告)号：WO2014078615A1

    公开(公告)日：2014-05-22

    申请号：PCT/US2013/070225

    申请日：2013-11-15

    Applicant: SIEMENS HEALTHCARE DIAGNOSTICS INC. ,  KAMEN, Ali ,  SINGH, Maneesh Kumar ,  POELSTERL, Sebastian ,  LADIC, Lance Anthony ,  COMANICIU, Dorin

    Inventor： KAMEN, Ali ,  SINGH, Maneesh Kumar ,  POELSTERL, Sebastian ,  LADIC, Lance Anthony ,  COMANICIU, Dorin

    IPC: G06F19/00

    CPC classification number: G06F19/345 ,  G06F19/00 ,  G06N3/0472 ,  G06N3/08 ,  G16H50/20

    Abstract: A method of identifying an optimum treatment for a patient suffering from coronary artery disease, comprising: (i) providing patient information selected from: (a) status in the patient of one or more coronary disease associated biomarkers; (b) one or more items of medical history information selected from prior condition history, intervention history and medication history; (c) one or more items of diagnostic history, if the patient has a diagnostic history; and (d) one or more items of demographic data; (ii) aggregating the patient information in: (a) a Bayesian network; (b) a machine learning and neural network; (c) a rule-based system; and (d) a regression-based system; (iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome.

    Abstract translation: 一种鉴定患有冠状动脉疾病的患者的最佳治疗的方法，包括：（i）提供患者信息，所述患者信息选自：（a）患者中一种或多种冠状动脉疾病相关生物标志物的状态; （b）从先前情况史，干预史和用药史选择的一项或多项病史信息; （c）患者具有诊断史的一项或多项诊断史; 和（d）一个或多个人口统计数据项目; （ii）在以下方面聚合患者信息：（a）贝叶斯网络; （b）机器学习和神经网络; （c）基于规则的制度; 和（d）基于回归的系统; （iii）通过放置裸金属支架或药物涂层支架，导出包括经皮冠状动脉介入的每个干预的预测概率不良事件结果; 或通过冠状动脉旁路移植术; 和（iv）确定具有最低预测概率不良结果的干预。

    METHOD AND SYSTEM FOR MULTI-SCALE ANATOMICAL AND FUNCTIONAL MODELING OF CORONARY CIRCULATION
    6.
    发明申请
    METHOD AND SYSTEM FOR MULTI-SCALE ANATOMICAL AND FUNCTIONAL MODELING OF CORONARY CIRCULATION 审中-公开
    冠状循环的多尺度解剖学和功能建模方法与系统

    公开(公告)号：WO2013071219A1

    公开(公告)日：2013-05-16

    申请号：PCT/US2012/064604

    申请日：2012-11-12

    Applicant: SIEMENS CORPORATION ,  SHARMA, Puneet ,  ITU, Lucian Mihai ,  GEORGESCU, Bogdan ,  MIHALEF, Viorel ,  KAMEN, Ali ,  COMANICIU, Dorin

    Inventor： SHARMA, Puneet ,  ITU, Lucian Mihai ,  GEORGESCU, Bogdan ,  MIHALEF, Viorel ,  KAMEN, Ali ,  COMANICIU, Dorin

    IPC: G06F19/00

    CPC classification number: G06F19/12 ,  G06F19/00 ,  G06F19/321 ,  G16H50/30 ,  G16H50/50

    Abstract: A method and system for multi-scale anatomical and functional modeling of coronary circulation is disclosed. A patient-specific anatomical model of coronary arteries and the heart is generated from medical image data of a patient. A multi-scale functional model of coronary circulation is generated based on the patient-specific anatomical model. Blood flow is simulated in at least one stenosis region of at least one coronary artery using the multi-scale function model of coronary circulation. Hemodynamic quantities, such as fractional flow reserve (FFR), are computed to determine a functional assessment of the stenosis, and virtual intervention simulations are performed using the multi-scale function model of coronary circulation for decision support and intervention planning.

    Abstract translation: 公开了一种用于冠状循环多尺度解剖和功能建模的方法和系统。 冠状动脉和心脏的患者特异性解剖模型由患者的医学图像数据产生。 基于患者特异性解剖模型产生冠状动脉循环的多尺度功能模型。 使用冠状动脉循环的多尺度功能模型在至少一个冠状动脉的至少一个狭窄区域中模拟血流量。 计算血流动力学量，例如分数流量储备（FFR），以确定狭窄的功能评估，并使用冠状动脉循环的多尺度函数模型进行虚拟干预模拟，以进行决策支持和干预计划。

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