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105 条记录 (耗时 0.039 秒)

    Method and System for Up-Vector Detection for Ribs in Computed Tomography Volumes
    71.
    发明申请
    Method and System for Up-Vector Detection for Ribs in Computed Tomography Volumes 有权
    计算机断层扫描中肋骨上向量检测的方法和系统

    公开(公告)号：US20130070996A1

    公开(公告)日：2013-03-21

    申请号：US13602660

    申请日：2012-09-04

    申请人： David Liu ,  Hao Xu ,  Dijia Wu ,  Christian Tietjen ,  Grzegorz Soza ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    发明人： David Liu ,  Hao Xu ,  Dijia Wu ,  Christian Tietjen ,  Grzegorz Soza ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    IPC分类号： G06K9/48 ,  G06K9/62 ,  G06K9/00

    CPC分类号： G06K9/00 ,  G06K9/48 ,  G06K9/62

    摘要： A method and system for up-vector detection for ribs in a 3D medical image volume, such as a computed tomography (CT) volume is disclosed. A rib centerline of at least one rib is extracted in a 3D medical image volume. An up-vector is automatically detected at each of a plurality of centerline points of the rib centerline of the at least one rib. The up-vector at each centerline point can be detected using a trained regression function. Alternatively, the up-vector at each centerline point can be detected by detecting an ellipse shape in a cross-sectional rib image generated at each centerline point.

    摘要翻译： 公开了一种用于3D医学图像体积中的肋的上矢量检测的方法和系统，例如计算机断层摄影（CT）体积。 在3D医学图像体积中提取至少一个肋的肋中心线。 在至少一个肋的肋中心线的多个中心线点的每一个处自动检测向上矢量。 可以使用经过训练的回归函数检测每个中心线点处的向上矢量。 或者，可以通过在每个中心线点处产生的横截面肋图像中检测椭圆形状来检测每个中心线点处的向上矢量。

    System and method for quasi-real-time ventricular measurements from M-mode echocardiogram
    72.
    发明授权
    System and method for quasi-real-time ventricular measurements from M-mode echocardiogram 有权
    从M型超声心动图准准实时心室测量的系统和方法

    公开(公告)号：US08396531B2

    公开(公告)日：2013-03-12

    申请号：US12054094

    申请日：2008-03-24

    申请人： Shaohua Kevin Zhou ,  Feng Guo ,  John Jackson ,  Michael Brendel ,  Dorin Comaniciu

    发明人： Shaohua Kevin Zhou ,  Feng Guo ,  John Jackson ,  Michael Brendel ,  Dorin Comaniciu

    IPC分类号： A61B5/00

    CPC分类号： A61B8/08 ,  A61B5/1075 ,  A61B5/7267 ,  A61B6/503 ,  A61B8/0883 ,  A61B8/463 ,  A61B8/486 ,  G06K9/00523 ,  G06K9/00536 ,  G06K9/6257 ,  G06T7/60

    摘要： A method for measuring ventricular dimensions from M-mode echocardiograms, includes providing a digitized M-mode echocardiogram image, running a plurality of local classifiers, where each local classifier trained to detect a landmark on either an end-diastole (ED) line or an end-systole (ES) line in the image, recording all possible landmarks detected by the classifiers, where a search range in an N-dimensional parameter space defined by the landmarks for each dimension is reduced to a union of subsets, where each dimension of the parameter space corresponds a landmark, for each combination of possible landmarks, checking if an order of the landmarks is consistent with a known ordering of the landmarks, and if the order is consistent, running a global detector on each consistent combination of landmarks to find a landmark combination with a highest detection probability as a confirmed landmark detection, where the landmarks are used for measuring ventricular dimensions.

    摘要翻译： 一种用于从M型超声心动图测量心室尺寸的方法，包括提供数字化的M模式超声心动图图像，运行多个局部分类器，其中训练每个局部分类器以检测舒张末期（ED）线或 记录图像中的终点收缩（ES）线，记录由分类器检测到的所有可能的地标，其中由每个维度的地标定义的N维参数空间中的搜索范围被减少到子集的并集，其中每个维度 参数空间对应于地标，对于可能的地标的每个组合，检查地标的顺序是否与已知的地标的顺序一致，并且如果顺序一致，则在每个一致的地标组合上运行全局检测器以找到 具有最高检测概率的地标组合，作为确认的地标检测，其中地标被用于测量心室维度。

    System and method for learning relative distance in a shape space using image based features
    75.
    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。

    Scalable Semantic Image Search
    76.
    发明申请
    Scalable Semantic Image Search 审中-公开
    可扩展语义图像搜索

    公开(公告)号：US20080027917A1

    公开(公告)日：2008-01-31

    申请号：US11767920

    申请日：2007-06-25

    申请人： Saikat Mukherjee ,  Shaohua Kevin Zhou ,  Xiang Zhou ,  Martin Huber ,  Jorg Freund ,  Volker Tresp ,  Sonja Zillner ,  Alok Gupta ,  Dorin Comaniciu

    发明人： Saikat Mukherjee ,  Shaohua Kevin Zhou ,  Xiang Zhou ,  Martin Huber ,  Jorg Freund ,  Volker Tresp ,  Sonja Zillner ,  Alok Gupta ,  Dorin Comaniciu

    IPC分类号： G06F17/30

    CPC分类号： G06F16/583 ,  G06N5/022

    摘要： A computer-implemented system for searching a plurality of images for an image of interest including a database of semantic image representations corresponding to the plurality of images, wherein the semantic image representations link a semantic model of clinical properties, a syntactic model of high level image properties and an image vocabulary of low level image properties, a set of queries associated with the semantic image representations, and a semantic search engine, embodied as computer readable code executed by a processor, for receiving a search query, selecting at least one of the set of queries based on the search query, and searching the plurality of images for the image of interest by comparing the plurality of images against the semantic image representations associated with a selected query.

    摘要翻译： 一种用于搜索感兴趣的图像的多个图像的计算机实现的系统，包括与多个图像相对应的语义图像表示的数据库，其中所述语义图像表示链接临床属性的语义模型，高级图像的句法模型 低级图像属性的属性和图像词汇表，与语义图像表示相关联的一组查询，以及体现为由处理器执行的计算机可读代码的语义搜索引擎，用于接收搜索查询，选择至少一个 基于搜索查询的查询集合，以及通过将多个图像与与所选择的查询相关联的语义图像表示进行比较来搜索多个图像中的感兴趣图像。

    Method and system for detection and tracking of coronary sinus catheter electrodes in fluoroscopic images
    78.
    发明授权
    Method and system for detection and tracking of coronary sinus catheter electrodes in fluoroscopic images 有权
    荧光镜检查和跟踪冠状静脉窦导管电极的方法和系统

    公开(公告)号：US08892186B2

    公开(公告)日：2014-11-18

    申请号：US13229855

    申请日：2011-09-12

    申请人： Wen Wu ,  Terrence Chen ,  Peng Wang ,  Norbert Strobel ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    发明人： Wen Wu ,  Terrence Chen ,  Peng Wang ,  Norbert Strobel ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    IPC分类号： A61B5/05 ,  G06T7/00 ,  G06T7/20 ,  A61B19/00

    CPC分类号： G06T7/0014 ,  A61B2034/2065 ,  A61B2090/376 ,  G06K2209/057 ,  G06T7/20 ,  G06T2207/10121 ,  G06T2207/30021 ,  G06T2207/30048

    摘要： A method and system for detecting and tracking coronary sinus (CS) catheter electrodes in a fluoroscopic image sequence is disclosed. An electrode model is initialized in a first frame of the fluoroscopic image sequence based on input locations of CS sinus catheter electrodes in the first frame. The electrode model is tracked in subsequent frames of the fluoroscopic image sequence by detecting electrode position candidates in the subsequent frames of the fluoroscopic image sequence using at least one trained electrode detector, generating electrode model candidates in the subsequent frames based on the detected electrode position candidates, calculating a probability score for each of the electrode model candidates, and selecting an electrode model candidate based on the probability score.

    摘要翻译： 公开了一种用于在荧光镜图像序列中检测和跟踪冠状窦（CS）导管电极的方法和系统。 基于第一帧中的CS窦导管电极的输入位置，在荧光镜图像序列的第一帧中初始化电极模型。 通过使用至少一个经过训练的电极检测器检测荧光镜像图像序列的后续帧中的电极位置候选物，在荧光图像序列的后续帧中跟踪电极模型，基于检测到的电极位置候选产生后续帧中的电极模型候选 计算每个电极模型候选的概率分数，并且基于概率分数来选择电极模型候选。