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91. 发明申请

US20120078097A1 COMPUTERIZED CHARACTERIZATION OF CARDIAC MOTION IN MEDICAL DIAGNOSTIC ULTRASOUND 审中-公开
标题翻译：医学诊断超声心脏运动的计算机表征
公开(公告)号：US20120078097A1
公开(公告)日：2012-03-29
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
IPC分类号： A61B8/08
CPC分类号： A61B8/483 , A61B8/00 , A61B8/0883 , G06T7/251 , G06T2207/10136 , G06T2207/30048
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.
摘要翻译：提供了心脏壁运动的计算机化特征。用于心脏壁运动的量由超声数据的四维（即3D +时间）序列确定。处理器自动处理体积数据以通过序列定位心脏壁，并从心脏壁位置或运动计算量。使用各种机器学习来定位和跟踪心脏壁，例如使用从训练数据学习的运动，用于初始定位心脏壁和运动，斑点跟踪，边界检测和用于跟踪另一机器学习的质量保护线索分类器当序列延伸多个周期时，循环被自动划分为心脏壁的独立跟踪。来自一个周期的心脏壁可用于传播到另一周期以初始化跟踪。每个循环中的独立跟踪可能会减少或避免由于漂移引起的不准确。

92. 发明申请

US20110301466A1 CARDIAC FLOW QUANTIFICATION WITH VOLUMETRIC IMAGING DATA 有权
标题翻译：具有体积成像数据的心脏流量定量
公开(公告)号：US20110301466A1
公开(公告)日：2011-12-08
申请号：US13151803
申请日：2011-06-02
申请人： Yang Wang , Bogdan Georgescu , Saurabh Datta , Dorin Comaniciu
发明人： Yang Wang , Bogdan Georgescu , Saurabh Datta , Dorin Comaniciu
IPC分类号： A61B8/06
CPC分类号： A61B8/065 , A61B6/503 , A61B8/06 , A61B8/0883 , A61B8/13 , G01S15/584 , G01S15/8979 , G06T5/002 , G06T7/0016 , G06T2207/10136 , G06T2207/20182 , G06T2207/30048 , G06T2207/30104
摘要： A method quantifies cardiac volume flow for an imaging sequence. The method includes receiving data representing three-dimensions and color Doppler flow data over a plurality of frames, constructing a ventricular model based on the data representing three-dimensions for the plurality of frames, the ventricular model including a sampling plane configured to measure the cardiac volume flow, computing volume flow samples based on the sampling plane and the color Doppler flow data, and correcting the volume flow samples for aliasing based on volumetric change in the ventricular model between successive frames of the plurality of frames.
摘要翻译：一种方法量化成像序列的心脏体积流量。该方法包括在多个帧上接收表示三维和彩色多普勒流数据的数据，基于代表多个帧的三维的数据构建心室模型，心室模型包括被配置成测量心脏的采样平面体积流量，基于采样平面和彩色多普勒流数据的计算体积流量样本，以及基于多个帧的连续帧之间的心室模型的体积变化来校正用于混叠的体积流量样本。

93. 发明授权

US08948484B2 Method and system for automatic view planning for cardiac magnetic resonance imaging acquisition 有权
标题翻译：心脏磁共振成像采集自动视图规划方法与系统
公开(公告)号：US08948484B2
公开(公告)日：2015-02-03
申请号：US13293239
申请日：2011-11-10
申请人： Xiaoguang Lu , Jens Guehring , Marie-Pierre Jolly , Bogdan Georgescu , Carmel Hayes , Peter Speier , Michaela Schmidt , Xiaoming Bi , Randall Kroeker , Dorin Comaniciu , Edgar Mueller
发明人： Xiaoguang Lu , Jens Guehring , Marie-Pierre Jolly , Bogdan Georgescu , Carmel Hayes , Peter Speier , Michaela Schmidt , Xiaoming Bi , Randall Kroeker , Dorin Comaniciu , Edgar Mueller
IPC分类号： G06K9/00 , G06K9/68 , G06K9/62
CPC分类号： G06K9/6857 , G06K9/6282
摘要： A method and system for automated view planning for cardiac magnetic resonance imaging (MRI) acquisition is disclosed. The method and system automatically generate a full scan prescription using a single 3D MRI volume. The left ventricle (LV) is segmented in the 3D MRI volume. Cardiac landmarks are detected in the automatically prescribed slices. A full scan prescription, including a short axis stack and 2-chamber, 3-chamber, and 4-chamber views, is automatically generated based on cardiac anchors provided by the segmented left ventricle and the detected cardiac landmarks in the 3D MRI volume.
摘要翻译：公开了用于心脏磁共振成像（MRI）采集的自动视图规划的方法和系统。该方法和系统使用单个3D MRI体积自动生成全扫描处方。左心室（LV）在3D MRI体积中分段。在自动规定的切片中检测到心脏地标。基于由分割的左心室提供的心脏锚定点和3D MRI体积中检测到的心脏地标，自动生成全扫描处方，包括短轴堆叠和2室，3室和4室视图。

94. 发明授权

US08218849B2 Method and system for automatic landmark detection using discriminative joint context 有权
标题翻译：使用区分联合上下文进行自动地标检测的方法和系统
公开(公告)号：US08218849B2
公开(公告)日：2012-07-10
申请号：US12549461
申请日：2009-08-28
申请人： Xiaoguang Lu , Bogdan Georgescu , Dorin Comaniciu , Arne Littmann , Edgar Mueller
发明人： Xiaoguang Lu , Bogdan Georgescu , Dorin Comaniciu , Arne Littmann , Edgar Mueller
IPC分类号： A61B6/03
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。

95. 发明授权

US08194955B2 Method and system for detection of contrast injection in fluoroscopic image sequences 有权
标题翻译：荧光图像序列中对比度注入检测方法和系统
公开(公告)号：US08194955B2
公开(公告)日：2012-06-05
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： G06K9/00
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。

96. 发明授权

US08121367B2 Method and system for vessel segmentation in fluoroscopic images 有权
标题翻译：荧光镜图像中血管分割的方法和系统
公开(公告)号：US08121367B2
公开(公告)日：2012-02-21
申请号：US12229663
申请日：2008-08-26
申请人： Richard Socher , Adrian Barbu , Bogdan Georgescu , Wei Zhang , Peter Durlak , Stefan Böhm , Dorin Comaniciu
发明人： Richard Socher , Adrian Barbu , Bogdan Georgescu , Wei Zhang , Peter Durlak , Stefan Böhm , 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。

97. 发明授权

US08050482B2 System and method for online optimization of guidewire visibility in fluoroscopic systems 有权
标题翻译：在荧光镜系统中在线优化导丝可视性的系统和方法
公开(公告)号：US08050482B2
公开(公告)日：2011-11-01
申请号：US11860588
申请日：2007-09-25
申请人： Adrian Barbu , Vassilis Athitsos , Bogdan Georgescu , Peter Durlak , Dorin Comaniciu
发明人： Adrian Barbu , Vassilis Athitsos , Bogdan Georgescu , Peter Durlak , Dorin Comaniciu
IPC分类号： G06K9/00
CPC分类号： A61B6/12 , G06T5/002 , G06T5/003 , G06T5/20 , G06T2207/10121 , G06T2207/30021 , G06T2207/30048 , G06T2207/30101
摘要： A method for online optimization of guidewire visibility in fluoroscopic images includes providing an digitized image acquired from a fluoroscopic imaging system, the image comprising an array of intensities corresponding to a 2-dimensional grid of pixels, detecting a guidewire in the fluoroscopic image, enhancing the visibility of the guidewire in the fluoroscopic image, calculating a visibility measure of the guidewire in the fluoroscopic image, and readjusting acquisition parameters of the fluoroscopic imaging system wherein the guidewire visibility is improved.
摘要翻译：一种用于在荧光镜图像中在线优化导丝可视性的方法包括提供从荧光成像系统获取的数字化图像，所述图像包括对应于像素的二维网格的强度阵列，检测透视图像中的导丝，增强在透视图像中的导丝的可视性，计算透视图像中的导丝的可见度测量，以及重新调整荧光镜成像系统的获取参数，其中导丝可视性得到改善。

98. 发明授权

US07995820B2 System and method for detection of fetal anatomies from ultrasound images using a constrained probabilistic boosting tree 有权
标题翻译：使用约束概率增强树从超声图像中检测胎儿解剖结构的系统和方法
公开(公告)号：US07995820B2
公开(公告)日：2011-08-09
申请号：US12056107
申请日：2008-03-26
申请人： Gustavo Henrique Monteiro de Barros Carneiro , Bogdan Georgescu , Sara Good , Dorin Comaniciu
发明人： Gustavo Henrique Monteiro de Barros Carneiro , Bogdan Georgescu , Sara Good , Dorin Comaniciu
IPC分类号： G06K9/00
CPC分类号： G06K9/46 , A61B8/0866 , G06K9/3233 , G06K9/38 , G06K9/4614 , G06K9/6282 , G06K2009/366 , G06K2209/051
摘要： A method for detecting fetal anatomic features in ultrasound images includes providing an ultrasound image of a fetus, specifying an anatomic feature to be detected in a region S determined by parameter vector θ, providing a sequence of probabilistic boosting tree classifiers, each with a pre-specified height and number of nodes. Each classifier computes a posterior probability P(y|S) where yε{−1,+1}, with P(y=+1|S) representing a probability that region S contains the feature, and P(y=−1|S) representing a probability that region S contains background information. The feature is detected by uniformly sampling a parameter space of parameter vector θ using a first classifier with a sampling interval vector used for training said first classifier, and having each subsequent classifier classify positive samples identified by a preceding classifier using a smaller sampling interval vector used for training said preceding classifier. Each classifier forms a union of its positive samples with those of the preceding classifier.
摘要翻译：一种用于检测超声图像中的胎儿解剖特征的方法，包括提供胎儿的超声图像，指定在由参数矢量和姿势确定的区域S中要检测的解剖特征;提供一系列概率增强树分类器，每个具有预先指定的高度和节点数。每个分类器计算出一个后验概率P（y | S），其中y（e）= { - 1，+ 1}，其中P（y = + 1 | S）表示区域S包含特征的概率，P（y = -1 | S），表示区域S包含背景信息的概率。通过对参数矢量和参数的参数空间进行均匀采样来检测该特征; 使用具有用于训练所述第一分类器的采样间隔向量的第一分类器，并且每个后续分类器使用用于训练所述先前分类器的较小采样间隔向量来对由先前分类器标识的正样本进行分类。每个分类器形成其正样本与上一分类器的并集。

99. 发明授权

US07949173B2 Method and system for regression-based object detection in medical images 有权
标题翻译：医学图像中基于回归的物体检测方法与系统
公开(公告)号：US07949173B2
公开(公告)日：2011-05-24
申请号：US11866572
申请日：2007-10-03
申请人： Shaohua Kevin Zhou , Jinghao Zhou , Bogdan Georgescu , Dorin Comaniciu
发明人： Shaohua Kevin Zhou , Jinghao Zhou , Bogdan Georgescu , Dorin Comaniciu
IPC分类号： G06K9/00 , A61B6/00
CPC分类号： G06K9/00 , G06K9/6256 , G06K9/72 , G06K2209/05
摘要： A method and system for regression-based object detection in medical images is disclosed. A regression function for predicting a location of an object in a medical image based on an image patch is trained using image-based boosting ridge regression (IBRR). The trained regression function is used to determine a difference vector based on an image patch of a medical image. The difference vector represents the difference between the location of the image patch and the location of a target object. The location of the target object in the medical image is predicted based on the difference vector determined by the regression function.
摘要翻译：公开了一种用于医学图像中基于回归的物体检测的方法和系统。使用基于图像的增强脊回归（IBRR）训练用于基于图像块预测医学图像中的对象的位置的回归函数。训练回归函数用于基于医学图像的图像块来确定差分矢量。差分向量表示图像块的位置与目标对象的位置之间的差异。基于由回归函数确定的差分向量来预测目标对象在医学图像中的位置。

100. 发明授权

US07831074B2 System and method for using a similarity function to perform appearance matching in image pairs 有权
标题翻译：使用相似度函数执行图像对中的外观匹配的系统和方法
公开(公告)号：US07831074B2
公开(公告)日：2010-11-09
申请号：US11539989
申请日：2006-10-10
申请人： Shaohua Kevin Zhou , Jie Shao , Jonathan Dowdall , Adrian Barbu , Bogdan Georgescu , Dorin Comaniciu
发明人： Shaohua Kevin Zhou , Jie Shao , Jonathan Dowdall , Adrian Barbu , Bogdan Georgescu , Dorin Comaniciu
IPC分类号： G06K9/00 , G06K9/62 , H04N5/225
CPC分类号： G06K9/6257 , G06K2209/05 , G06T7/33 , G06T2207/10124 , G06T2207/10132 , G06T2207/30048
摘要： The present invention is directed to a method for populating a database with a set of images of an anatomical structure. The database is used to perform appearance matching in image pairs of the anatomical structure. A set of image pairs of anatomical structures is received, where each image pair is annotated with a plurality of location-sensitive regions that identify a particular aspect of the anatomical structure. Weak learners are iteratively selected and an image patch is identified. A boosting process is used to identify a strong classifier based on responses to the weak learners applied to the identified image patch for each image pair. The responses comprise a feature response and a location response associated with the image patch. Positive and negative image pairs are generated. The positive and negative image pairs are used to learn a similarity function. The learned similarity function and iteratively selected weak learners are stored in the database.
摘要翻译：本发明涉及一种用解剖结构的一组图像填充数据库的方法。该数据库用于在解剖结构的图像对中执行外观匹配。接收一组解剖结构的图像对，其中每个图像对用多个识别解剖结构的特定方面的位置敏感区域注释。迭代选择弱学习者，并识别图像补丁。基于对应用于每个图像对的所识别的图像补丁的弱学习者的响应，使用增强过程来识别强分类器。响应包括与图像块相关联的特征响应和位置响应。产生正负图像对。正负图像对用于学习相似度函数。学习的相似度函数和迭代选择的弱学习者存储在数据库中。

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