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公开(公告)号：US07804999B2
公开(公告)日：2010-09-28
申请号：US11372782
申请日：2006-03-10
CPC分类号： G06K9/6256 , G06K2009/00322 , G06K2209/05
摘要： A method for performing image based regression using boosting to infer an entity that is associated with an image of an object is disclosed. A regression function for a plurality of images is learned in which for each image the associated entity is known. The learned regression function is used to predict an entity associated with an image in which the entity is not known.
摘要翻译： 公开了一种使用增强来执行基于图像的回归的方法来推断与对象的图像相关联的实体。 学习用于多个图像的回归函数，其中对于每个图像，相关联的实体是已知的。 学习的回归函数用于预测与实体不知道的图像相关联的实体。
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公开(公告)号：US20100240996A1
公开(公告)日：2010-09-23
申请号：US12702036
申请日：2010-02-08
申请人： Razvan Ioan Ionasec , Ingmar Voigt , Yang Wang , Bogdan Georgescu , Helene C. Houle , Dorin Comaniciu , Fernando Vega-Higuera
发明人： Razvan Ioan Ionasec , Ingmar Voigt , Yang Wang , Bogdan Georgescu , Helene C. Houle , Dorin Comaniciu , Fernando Vega-Higuera
CPC分类号： G06T7/0016 , G06T7/251 , G06T7/262 , G06T7/277 , G06T2207/10016 , G06T2207/10076 , G06T2207/10136 , G06T2207/20016 , G06T2207/30048 , G06T2207/30241
摘要： Heart valve operation is assessed with patient-specific medical diagnostic imaging data. To deal with the complex motion of the passive valve tissue, a hierarchal model is used. Rigid global motion of the overall valve, non-rigid local motion of landmarks of the valve, and surface motion of the valve are modeled sequentially. For the non-rigid local motion, a spectral trajectory approach is used in the model to determine location and motion of the landmarks more efficiently than detection and tracking. Given efficiencies in processing, more than one valve may be modeled at a same time. A graphic overlay representing the valve in four dimensions and/or quantities may be provided during an imaging session. One or more of these features may be used in combination or independently.
摘要翻译： 心脏瓣膜手术用患者特定的医学诊断成像数据进行评估。 为了处理被动瓣膜组织的复杂运动，使用了层次模型。 总体阀门的刚性全局运动，阀门的标志的非刚性局部运动以及阀门的表面运动被依次建模。 对于非刚性局部运动，在模型中使用频谱轨迹方法，以比检测和跟踪更有效地确定地标的位置和运动。 在处理效率方面，可以同时对多个阀进行建模。 可以在成像会话期间提供表示四维和/或数量的阀的图形覆盖。 这些特征中的一个或多个可以组合使用或独立使用。
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33.发明申请Method and System for Automatic Landmark Detection Using Discriminative Joint Context 有权使用歧义联合上下文的自动地标检测方法与系统公开(公告)号：US20100067764A1
公开(公告)日：2010-03-18
申请号：US12549461
申请日：2009-08-28
IPC分类号： G06K9/00
CPC分类号： G06K9/72 , G06T7/13 , G06T7/73 , G06T2207/10088 , G06T2207/20164 , G06T2207/30048
摘要： A method and system for detecting anatomic landmarks in medical images is disclosed. In order to detect multiple related anatomic landmarks, a plurality of landmark candidates are first detected individually using trained landmark detectors. A joint context is then generated for each combination of the landmark candidates. The best combination of landmarks in then determined based on the joint context using a trained joint context detector.
摘要翻译： 公开了用于检测医学图像中的解剖学标记的方法和系统。 为了检测多个相关的解剖标志，首先使用训练有素的地标检测器单独检测多个地标候选物。 然后为地标候选人的每个组合生成联合上下文。 使用训练有素的联合上下文检测器，基于联合上下文确定的地标的最佳组合。
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公开(公告)号：US07558402B2
公开(公告)日：2009-07-07
申请号：US10794476
申请日：2004-03-05
CPC分类号： G06K9/6247 , G06K9/3216 , G06K9/629 , G06K2209/051 , G06T7/215 , G06T7/251 , G06T2207/10132 , G06T2207/30048
摘要： A system and method for tracking a global shape of an object in motion is disclosed. One or more control points along an initial contour of the global shape are defined. Each of the one or more control points is tracked as the object is in motion. Uncertainty of a location of a control point in motion is represented using a number of techniques. The uncertainty to constrain the global shape is exploited using a prior shape model. In an alternative embodiment, multiple appearance models are built for each control point and the motion vectors produced by each model are combined in order to track the shape of the object. The movement of the shape of the object can be visually tracked using a display and color vectors.
摘要翻译： 公开了一种跟踪运动对象的全局形状的系统和方法。 定义沿着全局形状初始轮廓的一个或多个控制点。 一个或多个控制点中的每一个在物体运动时被跟踪。 使用许多技术来表示控制点在运动中的位置的不确定性。 使用先前的形状模型来利用限制全局形状的不确定性。 在替代实施例中，为每个控制点构建多个外观模型，并且组合由每个模型产生的运动矢量以跟踪对象的形状。 可以使用显示和颜色向量来可视地跟踪对象的形状的移动。
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35.发明授权System and method for detecting and matching anatomical structures using appearance and shape 有权使用外观和形状检测和匹配解剖结构的系统和方法公开(公告)号：US07536044B2
公开(公告)日：2009-05-19
申请号：US10991933
申请日：2004-11-18
CPC分类号： G06K9/6206 , G06K9/6256 , G06T7/12 , G06T7/149 , G06T7/251 , G06T2207/10132 , G06T2207/30048
摘要： A detection framework that matches anatomical structures using appearance and shape is disclosed. A training set of images are used in which object shapes or structures are annotated in the images. A second training set of images represents negative examples for such shapes and structures, i.e., images containing no such objects or structures. A classification algorithm trained on the training sets is used to detect a structure at its location. The structure is matched to a counterpart in the training set that can provide details about the structure's shape and appearance.
摘要翻译： 公开了一种使用外观和形状匹配解剖结构的检测框架。 使用图像的训练集，其中在图像中注释对象形状或结构。 图像的第二训练集表示这种形状和结构的负面例子，即不包含这样的对象或结构的图像。 训练集训练的分类算法用于检测其位置的结构。 该结构与训练集中的对应物匹配，可以提供关于结构形状和外观的细节。
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公开(公告)号：US20070071313A1
公开(公告)日：2007-03-29
申请号：US11372782
申请日：2006-03-10
申请人： Shaohua Zhou , Bogdan Georgescu , Xiang Zhou , Dorin Comaniciu
发明人： Shaohua Zhou , Bogdan Georgescu , Xiang Zhou , Dorin Comaniciu
IPC分类号： G06K9/62
CPC分类号： G06K9/6256 , G06K2009/00322 , G06K2209/05
摘要： A method for performing image based regression using boosting to infer an entity that is associated with an image of an object is disclosed. A regression function for a plurality of images is learned in which for each image the associated entity is known. The learned regression function is used to predict an entity associated with an image in which the entity is not known.
摘要翻译： 公开了一种使用增强来执行基于图像的回归的方法来推断与对象的图像相关联的实体。 学习用于多个图像的回归函数，其中对于每个图像，相关联的实体是已知的。 学习的回归函数用于预测与实体不知道的图像相关联的实体。
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37.发明申请Method and system for multi-modal component-based tracking of an object using robust information fusion 失效使用鲁棒信息融合的多模态组件跟踪对象的方法和系统公开(公告)号：US20050185826A1
公开(公告)日：2005-08-25
申请号：US11058784
申请日：2005-02-16
申请人： Bogdan Georgescu , Xiang Zhou , Dorin Comaniciu , R. Rao
发明人： Bogdan Georgescu , Xiang Zhou , Dorin Comaniciu , R. Rao
CPC分类号： G06K9/3216 , G06K9/6206 , G06T7/215 , G06T7/269
摘要： A system and method for tracking an object is disclosed. A video sequence including a plurality of image frames are received. A sample based representation of object appearance distribution is maintained. An object is divided into one or more components. For each component, its location and uncertainty with respect to the sample based representation are estimated. Variable-Bandwidth Density Based Fusion (VBDF) is applied to each component to determine a most dominant motion. The motion estimate is used to determine the track of the object.
摘要翻译： 公开了一种跟踪对象的系统和方法。 接收包括多个图像帧的视频序列。 维护对象外观分布的基于样本的表示。 一个对象被分成一个或多个组件。 对于每个组件，估计其相对于基于样本的表示的位置和不确定性。 基于可变带宽密度的融合（VBDF）应用于每个组件以确定最主要的运动。 运动估计用于确定对象的轨迹。
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公开(公告)号：US20190197199A9
公开(公告)日：2019-06-27
申请号：US13754174
申请日：2013-01-30
申请人： Tommaso Mansi , Bogdan Georgescu , Xudong Zheng , Ali Kamen , Dorin Comaniciu
发明人： Tommaso Mansi , Bogdan Georgescu , Xudong Zheng , Ali Kamen , Dorin Comaniciu
IPC分类号： G06F17/50
CPC分类号： G06F17/5009 , A61B5/0044 , A61B5/055 , A61B8/0883 , A61B2576/023 , A61N1/3627 , A61N1/36514 , A61N1/36585 , G06T17/00 , G06T2210/41 , G09B23/30 , G16H50/50
摘要： A method and system for patient-specific planning of cardiac therapy, such as cardiac resynchronization therapy (CRT), based on preoperative clinical data and medical images, such as ECG data, magnetic resonance imaging (MRI) data, and ultrasound data, is disclosed. A patient-specific anatomical model of the left and right ventricles is generated from medical image data of a patient. A patient-specific computational heart model, which comprises cardiac electrophysiology, biomechanics and hemodynamics, is generated based on the patient-specific anatomical model of the left and right ventricles and clinical data. Simulations of cardiac therapies, such as CRT at one or more anatomical locations are performed using the patient-specific computational heart model. Changes in clinical cardiac parameters are then computed from the patient-specific model, constituting predictors of therapy outcome useful for therapy planning and optimization.
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公开(公告)号：US10321892B2
公开(公告)日：2019-06-18
申请号：US13234697
申请日：2011-09-16
申请人： Yang Wang , Bogdan Georgescu , Helene C. Houle , Dorin Comaniciu
发明人： Yang Wang , Bogdan Georgescu , Helene C. Houle , Dorin Comaniciu
摘要： Computerized characterization of cardiac wall motion is provided. Quantities for cardiac wall motion are determined from a four-dimensional (i.e., 3D+time) sequence of ultrasound data. A processor automatically processes the volume data to locate the cardiac wall through the sequence and calculate the quantity from the cardiac wall position or motion. Various machine learning is used for locating and tracking the cardiac wall, such as using a motion prior learned from training data for initially locating the cardiac wall and the motion prior, speckle tracking, boundary detection, and mass conservation cues for tracking with another machine learned classifier. Where the sequence extends over multiple cycles, the cycles are automatically divided for independent tracking of the cardiac wall. The cardiac wall from one cycle may be used to propagate to another cycle for initializing the tracking. Independent tracking in each cycle may reduce or avoid inaccuracies due to drift.
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公开(公告)号：US10296809B2
公开(公告)日：2019-05-21
申请号：US13780230
申请日：2013-02-28
申请人： Saikiran Rapaka , Tommaso Mansi , Bogdan Georgescu , Ali Kamen , Dorin Comaniciu
发明人： Saikiran Rapaka , Tommaso Mansi , Bogdan Georgescu , Ali Kamen , Dorin Comaniciu
摘要： A method and system for patient-specific cardiac electrophysiology is disclosed. Particularly, a patient-specific anatomical model of a heart is generated from medical image data of a patient, a level-set representation of the patient-specific anatomical model is generated of the heart on a Cartesian grid; and a transmembrane action potential at each node of the level-set representation of the of the patient-specific anatomical model of the heart is computed on a Cartesian grid.
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