System and Method For Using A Similarity Function To Perform Appearance Matching In Image Pairs
    61.
    发明申请
    System and Method For Using A Similarity Function To Perform Appearance Matching In Image Pairs 有权
    在图像对中使用相似性函数进行外观匹配的系统和方法

    公开(公告)号:US20070237370A1

    公开(公告)日:2007-10-11

    申请号:US11539989

    申请日:2006-10-10

    IPC分类号: G06K9/00

    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。

    Method for performing image based regression using boosting
    62.
    发明申请
    Method for performing image based regression using boosting 有权
    使用升压进行基于图像的回归的方法

    公开(公告)号:US20070071313A1

    公开(公告)日:2007-03-29

    申请号:US11372782

    申请日:2006-03-10

    IPC分类号: G06K9/62

    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。

    Method and system for multi-modal component-based tracking of an object using robust information fusion
    63.
    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

    IPC分类号: G06K9/64 G06T7/20 G06K9/00

    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。

    Computerized characterization of cardiac motion in medical diagnostic ultrasound

    公开(公告)号:US10321892B2

    公开(公告)日:2019-06-18

    申请号:US13234697

    申请日:2011-09-16

    IPC分类号: A61B8/00 A61B8/08 G06T7/246

    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.

    Cardiac flow quantification with volumetric imaging data
    68.
    发明授权
    Cardiac flow quantification with volumetric imaging data 有权
    心脏流量定量与体积成像数据

    公开(公告)号:US08696579B2

    公开(公告)日:2014-04-15

    申请号:US13151803

    申请日:2011-06-02

    IPC分类号: A61B8/00

    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。