公开(公告)号：US07555151B2

公开(公告)日：2009-06-30

申请号：US11218018

申请日：2005-09-01

申请人： Dorin Comaniciu ,  Bogdan Georgescu ,  Jing Xiao ,  Xiang Zhou

发明人： Dorin Comaniciu ,  Bogdan Georgescu ,  Jing Xiao ,  Xiang Zhou

IPC分类号： G06K9/00

CPC分类号： G06K9/3216 ,  A61B8/08 ,  A61B8/0883 ,  A61B8/463 ,  A61B8/483 ,  G06K2209/051 ,  G06T7/0016 ,  G06T7/12 ,  G06T7/149 ,  G06T7/246 ,  G06T7/277 ,  G06T2200/04 ,  G06T2200/24 ,  G06T2207/10136 ,  G06T2207/30048 ,  Y10S128/922

摘要： A system and method for defining and tracking a deformable shape of a candidate anatomical structure wall in a three dimensional (3D) image is disclosed. The shape of the candidate anatomical structure is represented by a plurality of labeled 3D landmark points. At least one 3D landmark point of the deformable shape in an image frame is defined. A 3D cuboid is defined around the detected 3D landmark point. For each landmark point associated with the anatomical structure, its location and location uncertainty matrix is estimated in subsequent frames relative to the reference anatomical structures. A shape model is generated to represent dynamics of the deformable shape in subsequent image frames. The shape model includes statistical information from a training data set of 3D images of representative anatomical structures. The shape model is aligned to the deformable shape of the candidate anatomical structure. The shape model is fused with the deformable shape. A current shape of the candidate anatomical structure is estimated.

摘要翻译： 公开了一种在三维（3D）图像中定义和跟踪候选解剖结构壁的可变形形状的系统和方法。 候选解剖结构的形状由多个标记的3D地标点表示。 定义图像帧中的可变形形状的至少一个3D地标点。 3D立方体围绕检测到的3D地标点定义。 对于与解剖结构相关联的每个界标点，在相对于参考解剖结构的后续帧中估计其位置和位置不确定性矩阵。 生成形状模型以表示后续图像帧中的可变形形状的动态。 形状模型包括来自代表性解剖结构的3D图像的训练数据集的统计信息。 形状模型与候选解剖结构的可变形形状对齐。 形状模型与可变形的形状融合。 估计候选解剖结构的当前形状。

公开(公告)号：US20090123050A1

公开(公告)日：2009-05-14

申请号：US12288215

申请日：2008-10-17

申请人： Razvan Ionasec ,  Bogdan Georgescu ,  Helene C. Houle ,  Sebastian Vogt ,  Michael Scheuering ,  Estelle Camus ,  Dorin Comaniciu

发明人： Razvan Ionasec ,  Bogdan Georgescu ,  Helene C. Houle ,  Sebastian Vogt ,  Michael Scheuering ,  Estelle Camus ,  Dorin Comaniciu

IPC分类号： G06K9/00

CPC分类号： G06K9/00 ,  G06K2209/051 ,  G06T7/0016 ,  G06T7/251 ,  G06T17/20 ,  G06T2207/10076 ,  G06T2207/10136 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30048

摘要： A method and system for modeling the aortic valve in 4D image data, such as 4D CT and echocardiography, is disclosed. An initial estimate of a physiological aortic valve model is determined for at least one reference frame of a 4D image sequence based on anatomic features in the reference frame. The initial estimate is refined to generate a final estimate in the reference frame. A dynamic model of the aortic valve is then generated by estimating the physiological aortic valve model for each remaining frame of the 4D image sequence based on the final estimate in the reference frame. The aortic valve can be quantitatively evaluated using the dynamic model.

摘要翻译： 公开了用于4D图像数据建模主动脉瓣的方法和系统，如4D CT和超声心动图。 基于参考系中的解剖特征，为4D图像序列的至少一个参考帧确定生理主动脉瓣模型的初始估计。 改进初始估计以在参考系中产生最终估计。 然后通过基于参考框架中的最终估计估计4D图像序列的每个剩余帧的生理主动脉瓣模型来生成主动脉瓣的动态模型。 主动脉瓣可以使用动态模型进行定量评估。

公开(公告)号：US20090080745A1

公开(公告)日：2009-03-26

申请号：US12228911

申请日：2008-08-18

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

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

IPC分类号： G06K9/00

CPC分类号： G06T7/62 ,  G06T7/11 ,  G06T2207/10081 ,  G06T2207/30048

摘要： A method and system for measuring the volume of the left ventricle (LV) in a 3D medical image, such as a CT, volume is disclosed. Heart chambers are segmented in the CT volume, including at least the LV endocardium and the LV epicardium. An optimal threshold value is automatically determined based on voxel intensities within the LV endocardium and voxel intensities between the LV endocardium and the LV epicardium. Voxels within the LV endocardium are labeled as blood pool voxels or papillary muscle voxels based on the optimal threshold value. The LV volume can be measured excluding the papillary muscles based on the number of blood pool voxels, and the LV volume can be measured including the papillary muscles based on the total number of voxels within the LV endocardium.

摘要翻译： 公开了一种用于测量3D医学图像（例如CT）体积中的左心室（LV）的体积的方法和系统。 心室在CT体积中分段，至少包括LV心内膜和LV心外膜。 基于LV心内膜内的体素强度和LV心内膜与LV心外膜之间的体素强度自动确定最佳阈值。 基于最佳阈值将LV心内膜内的体素标记为血池体素或乳头肌肉体素。 基于血液池体素的数量可以除去乳头肌之外的LV体积，并且可以基于LV心内膜中的体素总数来测量LV体积，包括乳头肌。

公开(公告)号：US20090080728A1

公开(公告)日：2009-03-26

申请号：US12229663

申请日：2008-08-26

申请人： Richard Socher ,  Adrian Barbu ,  Bogdan Georgescu ,  Wei Zhang ,  Peter Durlak ,  Stefan Bohm ,  Dorin Comaniciu

发明人： Richard Socher ,  Adrian Barbu ,  Bogdan Georgescu ,  Wei Zhang ,  Peter Durlak ,  Stefan Bohm ,  Dorin Comaniciu

IPC分类号： G06K9/00

CPC分类号： G06K9/6256 ,  G06K2009/00932 ,  G06T7/12 ,  G06T7/162 ,  G06T2207/10121 ,  G06T2207/30048 ,  G06T2207/30101

摘要： A method and system for vessel segmentation in fluoroscopic images is disclosed. Hierarchical learning-based detection is used to perform the vessel segmentation. A boundary classifier is trained and used to detect boundary pixels of a vessel in a fluoroscopic image. A cross-segment classifier is trained and used to detect cross-segments connecting the boundary pixels. A quadrilateral classifier is trained and used to detect quadrilaterals connecting the cross segments. Dynamic programming is then used to combine the quadrilaterals to generate a tubular structure representing the vessel.

摘要翻译： 公开了一种用于荧光镜图像中血管分割的方法和系统。 使用基于层次学习的检测来执行血管分割。 边界分类器被训练并用于检测透视图像中血管的边界像素。 训练跨段分类器，用于检测连接边界像素的交叉段。 四边形分类器被训练并用于检测连接横截面的四边形。 然后使用动态规划来组合四边形以产生代表该容器的管状结构。

公开(公告)号：US20080107302A1

公开(公告)日：2008-05-08

申请号：US11872972

申请日：2007-10-16

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： G06K9/00

CPC分类号： G06K9/6256 ,  G06K9/00201 ,  G06K9/3233 ,  G06K2209/05 ,  G06T7/73 ,  G06T2207/30048

摘要： A method for detecting an object of interest in an input image includes the computer-implemented steps of: receiving an image, providing a multi-class pose classifier that identifies a plurality of pose features for estimating a pose of the object of interest, providing a plurality of cascades of serially-linked binary object feature classifiers, each cascade corresponding to different poses of the object of interest in the input image, selecting at least one of the cascades using the estimated pose, and employing the selected cascades to detect instances of the object of interest in the image.

摘要翻译： 一种用于在输入图像中检测感兴趣对象的方法包括以下计算机实现的步骤：接收图像，提供识别用于估计感兴趣对象的姿态的多个姿势特征的多类姿势分类器，提供 多个级联的串联二进制对象特征分类器，每个级联对应于输入图像中感兴趣对象的不同姿态，使用估计姿态选择级联中的至少一个，并且采用所选择的级联来检测 图像中感兴趣的对象。

公开(公告)号：US20070081705A1

公开(公告)日：2007-04-12

申请号：US11463341

申请日：2006-08-09

申请人： Gustavo Carneiro ,  Sara Good ,  Bogdan Georgescu ,  Paolo Favaro ,  Dorin Comaniciu

发明人： Gustavo Carneiro ,  Sara Good ,  Bogdan Georgescu ,  Paolo Favaro ,  Dorin Comaniciu

IPC分类号： G06K9/00

CPC分类号： G06K9/6226 ,  A61B8/0866 ,  A61B8/483 ,  A61B8/523 ,  G06K9/6289 ,  G06K9/6292 ,  G06T7/62 ,  G06T2207/30004

摘要： A method for segmenting and measuring anatomical structures in fetal ultrasound images includes the steps of providing a digitized ultrasound image of a fetus comprising a plurality of intensities corresponding to a domain of points on a 3-dimensional grid, providing a plurality of classifiers trained to detect anatomical structures in said image of said fetus, and segmenting and measuring an anatomical structure using said image classifiers by applying said elliptical contour classifiers to said fetal ultrasound image, wherein a plurality of 2-dimensional contours characterizing said anatomical structure are detected. The anatomical structure measurement can be combined with measurement of another anatomical structure to estimate gestational age of the fetus.

摘要翻译： 一种用于分割和测量胎儿超声图像中的解剖结构的方法包括以下步骤：提供胎儿的数字化超声图像，其包括对应于三维网格上的点的区域的多个强度，提供经过训练以检测的多个分类器 所述胎儿的所述图像中的解剖结构，以及使用所述图像分类器通过将所述椭圆轮廓分类器应用于所述胎儿超声图像来分割和测量解剖结构，其中检测表征所述解剖结构的多个二维轮廓。 解剖结构测量可以与另一种解剖结构的测量相结合，以估计胎儿的胎龄。

公开(公告)号：US07072494B2

公开(公告)日：2006-07-04

申请号：US11058784

申请日：2005-02-16

申请人： Bogdan Georgescu ,  Xiang Sean Zhou ,  Dorin Comaniciu ,  R. Bharat Rao

发明人： Bogdan Georgescu ,  Xiang Sean Zhou ,  Dorin Comaniciu ,  R. Bharat Rao

IPC分类号： G06K9/00

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。 保持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。

公开(公告)号：US20060074312A1

公开(公告)日：2006-04-06

申请号：US11186717

申请日：2005-07-21

申请人： Bogdan Georgescu ,  Xiang Zhou ,  Dorin Comaniciu ,  Sriram Krishnan

发明人： Bogdan Georgescu ,  Xiang Zhou ,  Dorin Comaniciu ,  Sriram Krishnan

IPC分类号： A61B8/00

CPC分类号： G06T7/215 ,  G06T7/12 ,  G06T2207/10132 ,  G06T2207/20068 ,  G06T2207/30004

摘要： Ultrasound signal information is detected from a sequence of images. A robust automated delineation of the border of the fan or ultrasound signal information in echocardiographic or other ultrasound image sequence is provided. The processor implemented delineation uses a single image or a sequence of images to better identify ultrasound signal data. Variation through a sequence generally identifies the signal area. Projecting the filtered variation information to two likely directions identifies approximate edge locations along the sides of the border. Robust regression fits lines to the edges to find accurate border locations. The bottom of the border is identified with a histogram of the variation information as a function of radius from an intersection of the fit lines.

摘要翻译： 从图像序列检测超声信号信息。 提供了在超声心动图或其他超声图像序列中对风扇或超声信号信息边界的鲁棒自动描绘。 实施描述的处理器使用单个图像或一系列图像来更好地识别超声信号数据。 通过序列的变化通常识别信号区域。 将过滤的变化信息投影到两个可能的方向，标识沿着边界两侧的近似边缘位置。 强大的回归符合边缘线以找到准确的边界位置。 边界的底部用变化信息的直方图识别为与拟合线交点相关的半径的函数。

公开(公告)号：US09277970B2

公开(公告)日：2016-03-08

申请号：US13946661

申请日：2013-07-19

申请人： Tommaso Mansi ,  Olivier Ecabert ,  Saikiran Rapaka ,  Bogdan Georgescu ,  Ali Kamen ,  Dorin Comaniciu

发明人： Tommaso Mansi ,  Olivier Ecabert ,  Saikiran Rapaka ,  Bogdan Georgescu ,  Ali Kamen ,  Dorin Comaniciu

IPC分类号： G06K9/00 ,  A61B19/00 ,  G06T19/20 ,  G06T7/00 ,  A61N7/02 ,  G06F19/00 ,  A61B18/14 ,  A61B5/042 ,  A61B18/02 ,  A61N1/362 ,  A61B18/00 ,  A61N1/39

CPC分类号： A61B34/10 ,  A61B5/042 ,  A61B18/02 ,  A61B18/1492 ,  A61B2018/00357 ,  A61B2018/00577 ,  A61B2018/00839 ,  A61B2034/104 ,  A61B2034/105 ,  A61B2034/107 ,  A61B2090/364 ,  A61B2090/3764 ,  A61N1/362 ,  A61N1/39 ,  A61N7/022 ,  G06T7/12 ,  G06T7/149 ,  G06T19/20 ,  G06T2207/10072 ,  G06T2207/20081 ,  G06T2207/20124 ,  G06T2207/30048 ,  G16H50/50

摘要： A method and system for patient-specific planning and guidance of an ablation procedure for cardiac arrhythmia is disclosed. A patient-specific anatomical heart model is generated based on pre-operative cardiac image data. The patient-specific anatomical heart model is registered to a coordinate system of intra-operative images acquired during the ablation procedure. One or more ablation site guidance maps are generated based on the registered patient-specific anatomical heart model and intra-operative patient-specific measurements acquired during the ablation procedure. The ablation site guidance maps may include myocardium diffusion and action potential duration maps. The ablation site guidance maps are generated using a computational model of cardiac electrophysiology which is personalized by fitting parameters of the cardiac electrophysiology model using the intra-operative patient-specific measurements. The ablation site guidance maps are displayed by a display device during the ablation procedure.

摘要翻译： 公开了一种用于患者特异性规划和指导心律失常消融手术的方法和系统。 基于手术前心脏图像数据生成患者特异性解剖心脏模型。 将患者特异性解剖心脏模型记录到在消融过程期间获取的手术中图像的坐标系。 基于注册的患者特异性解剖心脏模型和在消融过程期间获得的术中患者特异性测量来生成一个或多个消融部位引导图。 消融部位引导图可以包括心肌扩散和动作电位持续时间图。 使用心脏电生理学的计算模型产生消融部位指导图，其通过使用手术中患者特异性测量来拟合心脏电生理学模型的参数进行个性化。 在消融过程中，消融部位引导图由显示装置显示。

公开(公告)号：US08556814B2

公开(公告)日：2013-10-15

申请号：US12239898

申请日：2008-09-29

申请人： Gustavo Henrique Monteiro de Barros Carneiro ,  Fernando Amat ,  Bogdan Georgescu ,  Sara Good ,  Dorin Comaniciu

发明人： Gustavo Henrique Monteiro de Barros Carneiro ,  Fernando Amat ,  Bogdan Georgescu ,  Sara Good ,  Dorin Comaniciu

IPC分类号： A61B8/00

CPC分类号： A61B8/13 ,  A61B5/1075 ,  A61B5/7267 ,  A61B8/0816 ,  A61B8/0866 ,  A61B8/466 ,  G06F19/00 ,  G06F19/321 ,  G06K9/72 ,  G06K2209/05 ,  G06T7/11 ,  G06T2207/10136 ,  G06T2207/30044 ,  G16H50/20

摘要： A fetal parameter or anatomy is measured or detected from three-dimensional ultrasound data. An algorithm is machine-trained to detect fetal anatomy. Any machine training approach may be used. The machine-trained classifier is a joint classifier, such that one anatomy is detected using the ultrasound data and the detected location of another anatomy. The machine-trained classifier uses marginal space such that the location of anatomy is detected sequentially through translation, orientation and scale rather than detecting for all location parameters at once. The machine-trained classifier includes detectors for detecting from the ultrasound data at different resolutions, such as in a pyramid volume.

摘要翻译： 从三维超声数据测量或检测胎儿参数或解剖结构。 机器训练的算法用于检测胎儿解剖。 可以使用任何机器训练方法。 机器训练的分类器是联合分类器，使得使用超声数据和检测到的另一解剖结构的位置来检测一个解剖结构。 机器训练的分类器使用边缘空间，使得通过平移，取向和尺度顺序地检测解剖结构的位置，而不是一次检测所有位置参数。 机器训练分类器包括用于以不同分辨率例如金字塔体积的超声数据进行检测的检测器。