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    Method and System for Virtual Percutaneous Valve Implantation
    81.
    发明申请
    Method and System for Virtual Percutaneous Valve Implantation 审中-公开
    虚拟经皮瓣植入术的方法与系统

    公开(公告)号：US20110153286A1

    公开(公告)日：2011-06-23

    申请号：US12975714

    申请日：2010-12-22

    申请人： Dominik Zaeuner ,  Razvan Ioan Ionasec ,  Bogdan Georgescu ,  Yefeng Zheng ,  Dorin Comaniciu ,  Ingmar Voigt ,  Jan Boese

    发明人： Dominik Zaeuner ,  Razvan Ioan Ionasec ,  Bogdan Georgescu ,  Yefeng Zheng ,  Dorin Comaniciu ,  Ingmar Voigt ,  Jan Boese

    IPC分类号： G06F17/50

    CPC分类号： G06T19/00 ,  G06F19/321 ,  G06T17/00 ,  G06T2219/2004 ,  G16H50/50

    摘要： A method and system for virtual percutaneous valve implantation is disclosed. A patient-specific anatomical model of a heart valve is estimated based on 3D cardiac medical image data and an implant model representing a valve implant is virtually deployed into the patient-specific anatomical model of the heart valve. A library of implant models, each modeling geometrical properties of a corresponding valve implant, is maintained. The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select an implant type and size and deployment location and orientation for percutaneous valve implantation.

    摘要翻译： 公开了一种用于虚拟经皮瓣植入的方法和系统。 基于3D心脏医学图像数据估计心脏瓣膜的患者特异性解剖模型，并且代表瓣膜植入物的植入模型实际上部署到心脏瓣膜的患者特异性解剖模型中。 植入物模型库，每个建模相应的阀门植入物的几何特性被维持。 维护在库中的植入物模型实际上部署到心脏瓣膜的患者特异性解剖模型中，以选择用于经皮瓣膜植入的植入物类型和尺寸以及部署位置和取向。

    Method and System for Computational Modeling of the Aorta and Heart
    82.
    发明申请
    Method and System for Computational Modeling of the Aorta and Heart 有权
    主动脉和心脏计算建模方法与系统

    公开(公告)号：US20110060576A1

    公开(公告)日：2011-03-10

    申请号：US12825905

    申请日：2010-06-29

    申请人： Puneet Sharma ,  Bogdan Georgescu ,  Razvan Ioan Ionasec ,  Dorin Comaniciu

    发明人： Puneet Sharma ,  Bogdan Georgescu ,  Razvan Ioan Ionasec ,  Dorin Comaniciu

    IPC分类号： G06G7/60

    CPC分类号： G06T17/00 ,  G06F19/00 ,  G06T7/0012 ,  G06T2207/10072 ,  G06T2207/30048 ,  G16H50/20 ,  G16H50/50

    摘要： A method and system for generating a patient specific anatomical heart model is disclosed. A sequence of volumetric image data, such as computed tomography (CT), echocardiography, or magnetic resonance (MR) image data of a patient's cardiac region is received. A multi-component patient specific 4D geometric model of the heart and aorta estimated from the sequence of volumetric cardiac imaging data. A patient specific 4D computational model based on one or more of personalized geometry, material properties, fluid boundary conditions, and flow velocity measurements in the 4D geometric model is generated. Patient specific material properties of the aortic wall are estimated using the 4D geometrical model and the 4D computational model. Fluid Structure Interaction (FSI) simulations are performed using the 4D computational model and estimated material properties of the aortic wall, and patient specific clinical parameters are extracted based on the FSI simulations. Disease progression modeling and risk stratification are performed based on the patient specific clinical parameters.

    摘要翻译： 公开了一种用于产生患者特异性解剖心脏模型的方法和系统。 接收患者心脏区域的体积图像数据的序列，例如计算机断层摄影（CT），超声心动图或磁共振（MR）图像数据。 根据体积心脏成像数据序列估计的心脏和主动脉的多组分患者特定4D几何模型。 产生了基于4D几何模型中的个性化几何，材料特性，流体边界条件和流速测量中的一个或多个的患者特定4D计算模型。 使用4D几何模型和4D计算模型估计主动脉壁的患者特异性材料性质。 使用4D计算模型和主动脉壁的估计材料特性进行流体结构相互作用（FSI）模拟，并且基于FSI模拟提取患者特异性临床参数。 疾病进展模型和风险分层是根据患者的具体临床参数进行的。

    Method and System for Detecting 3D Anatomical Structures Using Constrained Marginal Space Learning
    84.
    发明申请
    Method and System for Detecting 3D Anatomical Structures Using Constrained Marginal Space Learning 有权
    使用约束边际空间学习检测3D解剖结构的方法和系统

    公开(公告)号：US20090304251A1

    公开(公告)日：2009-12-10

    申请号：US12471761

    申请日：2009-05-26

    申请人： Yefeng Zheng ,  Bogdan Georgescu ,  Haibin Ling ,  Michael Scheuering ,  Dorin Comaniciu

    发明人： Yefeng Zheng ,  Bogdan Georgescu ,  Haibin Ling ,  Michael Scheuering ,  Dorin Comaniciu

    IPC分类号： G06K9/00

    CPC分类号： G06K9/3233 ,  G06K2209/051 ,  G06T7/75 ,  G06T2207/10081 ,  G06T2207/30004

    摘要： A method and apparatus for detecting 3D anatomical objects in medical images using constrained marginal space learning (MSL) is disclosed. A constrained search range is determined for an input medical image volume based on training data. A first trained classifier is used to detect position candidates in the constrained search range. Position-orientation hypotheses are generated from the position candidates using orientation examples in the training data. A second trained classifier is used to detect position-orientation candidates from the position-orientation hypotheses. Similarity transformation hypotheses are generated from the position-orientation candidates based on scale examples in the training data. A third trained classifier is used to detect similarity transformation candidates from the similarity transformation hypotheses, and the similarity transformation candidates define the position, translation, and scale of the 3D anatomic object in the medical image volume.

    摘要翻译： 公开了一种使用受限边际空间学习（MSL）检测医学图像中3D解剖学对象的方法和装置。 基于训练数据确定输入医学图像体积的约束搜索范围。 第一训练分类器用于检测约束搜索范围内的位置候选。 使用训练数据中的取向示例从位置候选者生成位置取向假设。 第二训练分类器用于从位置定向假设检测位置方向候选。 基于训练数据中的比例示例，从位置定位候选生成相似度转换假设。 第三训练分类器用于从相似变换假设检测相似变换候选，并且相似变换候选定义医学图像体积中的3D解剖对象的位置，平移和比例。

    Method and system for dynamic pulmonary trunk modeling in computed tomography and magnetic resonance imaging
    87.
    发明申请
    Method and system for dynamic pulmonary trunk modeling in computed tomography and magnetic resonance imaging 有权
    计算机断层扫描和磁共振成像中动态肺动脉造影的方法和系统

    公开(公告)号：US20090154785A1

    公开(公告)日：2009-06-18

    申请号：US12315343

    申请日：2008-12-01

    申请人： Michael Lynch ,  Razvan Ionasec ,  Bogdan Georgescu ,  Dorin Comaniciu ,  Dime Vitanovski

    发明人： Michael Lynch ,  Razvan Ionasec ,  Bogdan Georgescu ,  Dorin Comaniciu ,  Dime Vitanovski

    IPC分类号： G06T7/00

    CPC分类号： G06T7/38 ,  G06T7/33 ,  G06T2207/10076 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/30048

    摘要： A method and system for modeling the pulmonary trunk in 4D image data, such as 4D CT and MRI data, is disclosed. Bounding boxes are detected in frames of the 4D image data. Anatomic landmarks are detected in the frames of the 4D image data based on the bounding boxes. Ribs or centerlines of the pulmonary artery are detected in the frames of the 4D image data based on the anatomic landmarks, and a physiological pulmonary trunk model is fit the frames of the 4D image data based on the detected ribs and anatomic landmarks. The boundary of the pulmonary trunk is detected in order to refine the boundary of the pulmonary trunk model in the frames of the 4D image data, resulting in a dynamic model of the pulmonary trunk. The pulmonary trunk can be quantitatively evaluated using the dynamic model.

    摘要翻译： 公开了4D图像数据（如4D CT和MRI数据）对肺动脉干线进行建模的方法和系统。 在4D图像数据的帧中检测边界框。 基于边界框在4D图像数据的帧中检测解剖标志。 基于解剖标志，在4D图像数据的帧中检测肺动脉的肋或中心线，并且基于检测到的肋和解剖标志，生理性肺动脉干模型适合4D图像数据的帧。 检测肺动脉干的边界，以便在4D图像数据的帧中改善肺动脉干模型的边界，得到肺动脉的动态模型。 可以使用动态模型定量评估肺动脉干。

    Method and system for detection of contrast injection in fluoroscopic image sequences
    88.
    发明申请
    Method and system for detection of contrast injection in fluoroscopic image sequences 有权
    荧光图像序列中对比度注入检测方法和系统

    公开(公告)号：US20090090873A1

    公开(公告)日：2009-04-09

    申请号：US12231770

    申请日：2008-09-05

    申请人： Benjamin J. Sapp ,  Wei Zhang ,  Bogdan Georgescu ,  Simone Prummer ,  Dorin Comaniciu

    发明人： Benjamin J. Sapp ,  Wei Zhang ,  Bogdan Georgescu ,  Simone Prummer ,  Dorin Comaniciu

    IPC分类号： F21V9/16 ,  A61B6/00 ,  G06K9/00 ,  G01N33/48 ,  G01D18/00

    CPC分类号： G06K9/00 ,  G06K2209/05 ,  G06T7/0012

    摘要： A method and system for detecting a spatial and temporal location of a contrast injection in a fluoroscopic image sequence is disclosed. Training volumes generated by stacking a sequence of 2D fluoroscopic images in time order are annotated with ground truth contrast injection points. A heart rate is globally estimated for each training volume, and local frequency and phase is estimated in a neighborhood of the ground truth contrast injection point for each training volume. Frequency and phase invariant features are extracted from each training volume based on the heart rate, local frequency and phase, and a detector is trained based on the training volumes and the features extracted for each training volume. The detector can be used to detect the spatial and temporal location of a contrast injection in a fluoroscopic image sequence.

    摘要翻译： 公开了一种用于检测透视图像序列中的对比度注入的空间和时间位置的方法和系统。 通过以时间顺序堆叠一系列2D透视图像而产生的训练体积用地面真实对比度注入点注释。 对于每个训练体积，全局估计心率，并且在每个训练体积的地面真实对比度注入点的邻域中估计局部频率和相位。 基于心率，局部频率和相位从每个训练体积中提取频率和相位不变特征，并且基于训练量和针对每个训练体积提取的特征来训练检测器。 检测器可用于检测透视图像序列中对比度注入的空间和时间位置。

    Method and system for generating a four-chamber heart model
    89.
    发明申请
    Method and system for generating a four-chamber heart model 有权
    用于产生四室心脏模型的方法和系统

    公开(公告)号：US20080262814A1

    公开(公告)日：2008-10-23

    申请号：US12082143

    申请日：2008-04-09

    申请人： Yefeng Zheng ,  Adrian Barbu ,  Bogdan Georgescu ,  Michael Lynch ,  Michael Scheuering ,  Dorin Comaniciu

    发明人： Yefeng Zheng ,  Adrian Barbu ,  Bogdan Georgescu ,  Michael Lynch ,  Michael Scheuering ,  Dorin Comaniciu

    IPC分类号： G06G7/60

    CPC分类号： G06F19/3437 ,  G06F19/00 ,  G06F19/34 ,  G06T2207/30048 ,  G16H50/50

    摘要： A method and system for building a statistical four-chamber heart model from 3D volumes is disclosed. In order to generate the four-chamber heart model, each chamber is modeled using an open mesh, with holes at the valves. Based on the image data in one or more 3D volumes, meshes are generated and edited for the left ventricle (LV), left atrium (LA), right ventricle (RV), and right atrium (RA). Resampling to enforce point correspondence is performed during mesh editing. Important anatomic landmarks in the heart are explicitly represented in the four-chamber heart model of the present invention.

    摘要翻译： 公开了一种用于从3D体积构建统计四室心脏模型的方法和系统。 为了产生四腔心脏模型，每个腔室都使用开放的网格进行建模，在阀门处有孔。 基于一个或多个3D体积中的图像数据，为左心室（LV），左心房（LA），右心室（RV）和右心房（RA）生成并编辑网格。 在网格编辑期间执行重新采样以强制点对应。 在本发明的四腔心脏模型中明确地表示心脏中的重要解剖学标志。

    Component-Based Approach For Fast Left Ventricle Detection
    90.
    发明申请
    Component-Based Approach For Fast Left Ventricle Detection 审中-公开
    基于组件的快速左心室检测方法

    公开(公告)号：US20080086053A1

    公开(公告)日：2008-04-10

    申请号：US11866712

    申请日：2007-10-03

    申请人： Shaohua Zhou ,  Jingdan Zhang ,  Bogdan Georgescu ,  Dorin Comaniciu

    发明人： Shaohua Zhou ,  Jingdan Zhang ,  Bogdan Georgescu ,  Dorin Comaniciu

    IPC分类号： A61B8/00

    CPC分类号： A61B8/08 ,  A61B6/503

    摘要： A method for estimating a configuration of an internal structure within a medical image includes detecting a location of the internal structure. Component-based identification is performed within the detected location of the internal structure to identify a plurality of components. The configuration of the internal structure is estimated based on the relative position of the identified components.

    摘要翻译： 用于估计医学图像内部结构的配置的方法包括检测内部结构的位置。 在检测到的内部结构的位置内执行基于组件的识别以识别多个组件。 基于所识别的组件的相对位置来估计内部结构的配置。