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    SYSTEM AND METHOD FOR LEARNING RELATIVE DISTANCE IN A SHAPE SPACE USING IMAGE BASED FEATURES
    1.
    发明申请
    SYSTEM AND METHOD FOR LEARNING RELATIVE DISTANCE IN A SHAPE SPACE USING IMAGE BASED FEATURES 有权
    使用基于图像的特征在形状空间中学习相对距离的系统和方法

    公开(公告)号：US20070046696A1

    公开(公告)日：2007-03-01

    申请号：US11464851

    申请日：2006-08-16

    申请人： Yefeng Zheng ,  Xiang Zhou ,  Shaohua Zhou ,  Bogdan Georgescu ,  Dorin Comaniciu

    发明人： Yefeng Zheng ,  Xiang Zhou ,  Shaohua Zhou ,  Bogdan Georgescu ,  Dorin Comaniciu

    IPC分类号： G09G5/00

    CPC分类号： G06K9/6255 ,  G06K9/6206 ,  G06K9/6256

    摘要： A system and method for identifying a shape of an anatomical structure in an input image is disclosed. An input image is received and warped using a set of warping templates resulting in a set of warped images. An integral image is calculated for each warped image. Selected features are extracted based on the integral image. A boosted feature score is calculated for the combined selected features for each warped image. The warped images are ranked based on the boosted feature scores. A predetermined number of warped images are selected that have the largest feature scores. Each selected warped image is associated with its corresponding warping template. The corresponding warping templates are associated with stored shape models. The shape of the input image is identified based on the weighted average of the shapes models.

    摘要翻译： 公开了一种用于识别输入图像中的解剖结构的形状的系统和方法。 使用一组翘曲模板接收和扭曲输入图像，产生一组翘曲图像。 为每个弯曲图像计算整体图像。 基于积分图像提取所选特征。 对于每个弯曲图像的组合选定特征，计算提升的特征分数。 翘曲的图像根据提升的特征得分进行排名。 选择具有最大特征分数的预定数量的翘曲图像。 每个选择的变形图像与其相应的翘曲模板相关联。 相应的变形模板与存储的形状模型相关联。 基于形状模型的加权平均值来识别输入图像的形状。

    System and method for learning relative distance in a shape space using image based features
    2.
    发明授权
    System and method for learning relative distance in a shape space using image based features 有权
    使用基于图像的特征来学习形状空间中的相对距离的系统和方法

    公开(公告)号：US07603000B2

    公开(公告)日：2009-10-13

    申请号：US11464851

    申请日：2006-08-16

    申请人： Yefeng Zheng ,  Xiang Zhou ,  Shaohua Kevin Zhou ,  Bogdan Georgescu ,  Dorin Comaniciu

    发明人： Yefeng Zheng ,  Xiang Zhou ,  Shaohua Kevin Zhou ,  Bogdan Georgescu ,  Dorin Comaniciu

    IPC分类号： G06K9/60

    CPC分类号： G06K9/6255 ,  G06K9/6206 ,  G06K9/6256

    摘要： A system and method for identifying a shape of an anatomical structure in an input image is disclosed. An input image is received and warped using a set of warping templates resulting in a set of warped images. An integral image is calculated for each warped image. Selected features are extracted based on the integral image. A boosted feature score is calculated for the combined selected features for each warped image. The warped images are ranked based on the boosted feature scores. A predetermined number of warped images are selected that have the largest feature scores. Each selected warped image is associated with its corresponding warping template. The corresponding warping templates are associated with stored shape models. The shape of the input image is identified based on the weighted average of the shapes models.

    摘要翻译： 公开了一种用于识别输入图像中的解剖结构的形状的系统和方法。 使用一组翘曲模板接收和扭曲输入图像，产生一组翘曲图像。 为每个弯曲图像计算整体图像。 基于积分图像提取所选特征。 对于每个弯曲图像的组合选定特征，计算提升的特征分数。 翘曲的图像根据提升的特征得分进行排名。 选择具有最大特征分数的预定数量的翘曲图像。 每个选择的变形图像与其相应的翘曲模板相关联。 相应的变形模板与存储的形状模型相关联。 基于形状模型的加权平均值来识别输入图像的形状。

    Method for performing image based regression using boosting
    3.
    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

    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。

    Method and system for multi-modal component-based tracking of an object using robust information fusion
    5.
    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

    IPC分类号： G06K9/64 ,  G06T7/20 ,  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。 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。

    Method for database guided simultaneous multi slice object detection in three dimensional volumetric data
    7.
    发明申请
    Method for database guided simultaneous multi slice object detection in three dimensional volumetric data 有权
    三维体积数据中数据库引导同时多切片物体检测方法

    公开(公告)号：US20070036414A1

    公开(公告)日：2007-02-15

    申请号：US11502709

    申请日：2006-08-10

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

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

    IPC分类号： G06K9/00 ,  G06K9/62

    CPC分类号： G06T7/149 ,  G06T7/12 ,  G06T2207/10136 ,  G06T2207/20081 ,  G06T2207/30048

    摘要： The present invention is directed to a method for automatic detection and segmentation of a target anatomical structure in received three dimensional (3D) volumetric medical images using a database of a set of volumetric images with expertly delineated anatomical structures. A 3D anatomical structure detection and segmentation module is trained offline by learning anatomical structure appearance using the set of expertly delineated anatomical structures. A received volumetric image for the anatomical structure of interest is searched online using the offline learned 3D anatomical structure detection and segmentation module.

    摘要翻译： 本发明涉及一种使用具有专门描绘的解剖结构的一组体积图像的数据库来自动检测和分割接收的三维（3D）体积医学图像中的目标解剖结构的方法。 3D解剖结构检测和分割模块通过使用专门描绘的解剖结构集合学习解剖结构外观来进行离线训练。 使用离线学习的3D解剖结构检测和分割模块在线搜索用于感兴趣解剖结构的接收体积图像。

    System and method for tracking anatomical structures in three dimensional images
    10.
    发明授权
    System and method for tracking anatomical structures in three dimensional images 有权
    用于跟踪三维图像中解剖结构的系统和方法

    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。