利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

405 条记录 (耗时 0.026 秒)

    System and method for coronary digital subtraction angiography
    41.
    发明授权
    System and method for coronary digital subtraction angiography 有权
    冠状动脉数字减影血管造影的系统和方法

    公开(公告)号：US08094903B2

    公开(公告)日：2012-01-10

    申请号：US12157837

    申请日：2008-06-13

    申请人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

    发明人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

    IPC分类号： G06K9/03

    CPC分类号： A61B6/504 ,  A61B6/481 ,  G06T5/50 ,  G06T7/215 ,  G06T7/30 ,  G06T2207/10016 ,  G06T2207/10121 ,  G06T2207/30048 ,  G06T2207/30101

    摘要： A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image, and the mask image is warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

    摘要翻译： 公开了使用冠状动脉数字减影血管造影（DSA）提取冠脉血管荧光镜图像序列的方法和系统。 接收冠状动脉区域的一组掩模图像，并且接收冠状动脉区域的对比度图像序列。 对于每个对比图像，使用基于学习的血管段检测在对比图像中检测血管区域，并且基于检测到的血管区域确定造影剂图像的背景区域。 在掩模图像之一和对比度图像的背景区域之间估计背景运动，并且基于所估计的背景运动来对掩模图像进行翘曲以生成估计的背景层。 从对比图像中减去估计的背景层，以提取对比度图像的冠状血管层。

    System and method for detecting and tracking a guidewire in a fluoroscopic image sequence
    42.
    发明授权
    System and method for detecting and tracking a guidewire in a fluoroscopic image sequence 有权
    用于在透视图像序列中检测和跟踪导丝的系统和方法

    公开(公告)号：US07792342B2

    公开(公告)日：2010-09-07

    申请号：US11675678

    申请日：2007-02-16

    申请人： Adrian Barbu ,  Vassilis Athitsos ,  Bogdan Georgescu ,  Peter Durlak ,  Stefan Boehm ,  Dorin Comaniciu

    发明人： Adrian Barbu ,  Vassilis Athitsos ,  Bogdan Georgescu ,  Peter Durlak ,  Stefan Boehm ,  Dorin Comaniciu

    IPC分类号： G06K9/00

    CPC分类号： A61B6/12 ,  G06K9/48 ,  G06K2209/057

    摘要： A system and method for populating a database with a set of image sequences of an object is disclosed. The database is used to detect localization of a guidewire in the object. A set of images of anatomical structures is received in which each image is annotated to show a guidewire, catheter, wire tip and stent. For each given image a Probabilistic Boosting Tree (PBT) is used to detect short line segments of constant length in the image. Two segment curves are constructed from the short line segments. A discriminative joint shape and appearance model is used to classify each two segment curve. A shape of an n-segment curve is constructed by concatenating all the two segment curves. A guidewire curve model is identified that includes a start point, end point and the n-segment curve. The guidewire curve model is stored in the database.

    摘要翻译： 公开了一种使用一组对象的图像序列填充数据库的系统和方法。 数据库用于检测对象中导丝的定位。 接收一组解剖结构的图像，其中每个图像被注释以示出导丝，导管，线尖和支架。 对于每个给定的图像，使用概率增强树（PBT）来检测图像中恒定长度的短线段。 从短线段构建两段曲线。 使用歧视关节形状和外观模型对每个两段曲线进行分类。 通过连接所有两个段曲线构建n段曲线的形状。 识别出导线曲线模型，其包括起始点，终点和n段曲线。 导丝曲线模型存储在数据库中。

    System and method for coronary digital subtraction angiography
    43.
    发明申请
    System and method for coronary digital subtraction angiography 有权
    冠状动脉数字减影血管造影的系统和方法

    公开(公告)号：US20090010512A1

    公开(公告)日：2009-01-08

    申请号：US12157837

    申请日：2008-06-13

    申请人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

    发明人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

    IPC分类号： H05G1/64 ,  G06K9/00

    CPC分类号： A61B6/504 ,  A61B6/481 ,  G06T5/50 ,  G06T7/215 ,  G06T7/30 ,  G06T2207/10016 ,  G06T2207/10121 ,  G06T2207/30048 ,  G06T2207/30101

    摘要： A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image, and the mask image is warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

    摘要翻译： 公开了使用冠状动脉数字减影血管造影（DSA）提取冠脉血管荧光镜图像序列的方法和系统。 接收冠状动脉区域的一组掩模图像，并且接收冠状动脉区域的对比度图像序列。 对于每个对比图像，使用基于学习的血管段检测在对比图像中检测血管区域，并且基于检测到的血管区域确定造影剂图像的背景区域。 在掩模图像之一和对比度图像的背景区域之间估计背景运动，并且基于所估计的背景运动来对掩模图像进行翘曲以生成估计的背景层。 从对比图像中减去估计的背景层，以提取对比度图像的冠状血管层。

    Method and System for Object Detection Using Probabilistic Boosting Cascade Tree
    46.
    发明申请
    Method and System for Object Detection Using Probabilistic Boosting Cascade Tree 审中-公开
    使用概率提升级联树的对象检测方法和系统

    公开(公告)号：US20080071711A1

    公开(公告)日：2008-03-20

    申请号：US11856109

    申请日：2007-09-17

    申请人： Wei Zhang ,  Adrian Barbu ,  Yefeng Zheng ,  Dorin Comaniciu

    发明人： Wei Zhang ,  Adrian Barbu ,  Yefeng Zheng ,  Dorin Comaniciu

    IPC分类号： G06F15/18

    CPC分类号： G06N7/005 ,  G06K9/6257 ,  G06K2209/053

    摘要： A method and system for object detection using a probabilistic boosting cascade tree (PBCT) is disclosed. A PBCT is a machine learning based classifier having a structure that is driven by training data and determined during the training process without user input. In a PBCT training method, for each node in the PBCT, a classifier is trained for the node based on training data received at the node. The performance of the classifier trained for the node is then evaluated based on the training data. Based on the performance of the classifier, the node is set to either a cascade node or a tree node. If the performance indicates that the data is relatively easy to classify, the node can be set as a cascade node. If the performance indicates that the data is relatively difficult to classify, the node can be set as a tree node. The trained PBCT can then be used to detect objects or classify data. For example, a trained PBCT can be used to detect lymph nodes in CT volume data.

    摘要翻译： 公开了一种使用概率升压级联树（PBCT）进行物体检测的方法和系统。 PBCT是基于机器学习的分类器，其具有由训练数据驱动的结构，并且在训练过程中确定而不需要用户输入。 在PBCT训练方法中，对于PBCT中的每个节点，基于在节点处接收到的训练数据，为节点训练分类器。 然后根据训练数据对针对节点训练的分类器的性能进行评估。 基于分类器的性能，将节点设置为级联节点或树节点。 如果性能指示数据相对容易分类，则可以将节点设置为级联节点。 如果性能指示数据相对较难分类，则可以将节点设置为树节点。 然后，训练有素的PBCT可用于检测对象或对数据进行分类。 例如，训练有素的PBCT可用于检测CT体积数据中的淋巴结。

    System and Method For Simultaneously Subsampling Fluoroscopic Images and Enhancing Guidewire Visibility
    49.
    发明申请
    System and Method For Simultaneously Subsampling Fluoroscopic Images and Enhancing Guidewire Visibility 失效
    同时采样荧光图像和提高导丝可视性的系统和方法

    公开(公告)号：US20080107314A1

    公开(公告)日：2008-05-08

    申请号：US11860591

    申请日：2007-09-25

    申请人： Bogdan Georgescu ,  Peter Durlak ,  Vassilis Athitsos ,  Adrian Barbu ,  Dorin Comaniciu

    发明人： Bogdan Georgescu ,  Peter Durlak ,  Vassilis Athitsos ,  Adrian Barbu ,  Dorin Comaniciu

    IPC分类号： G06K9/00 ,  G06K9/40

    CPC分类号： G06T5/003 ,  G06T5/20 ,  G06T7/74 ,  G06T2207/10121 ,  G06T2207/20016 ,  G06T2207/30021

    摘要： A method for downsampling fluoroscopic images and enhancing guidewire visibility during coronary angioplasty includes providing a first digitized image, filtering the image with one or more steerable filters of different angular orientations, assigning a weight W and orientation O for each pixel based on the filter response for each pixel, wherein each pixel weight is assigned to a function of a maximum filter response magnitude and the pixel orientation is calculated from the angle producing the maximum filter response if the magnitude is greater than zero, wherein guidewire pixels have a higher weight than non-guidewire pixels, and downsampling the orientation and weights to calculate a second image of half the resolution of the first image, wherein the downsampling accounts for the orientation and higher weight assigned to the guidewire pixels.

    摘要翻译： 用于在冠状动脉血管成形术期间对荧光透视图像进行下采样并增强导丝线可视性的方法包括提供第一数字化图像，用一个或多个不同角取向的可转向滤光片过滤图像，基于滤波器响应为每个像素分配权重W和取向O 每个像素，其中每个像素权重被分配给最大滤波器响应幅度的函数，并且如果幅度大于零，则从产生最大滤波器响应的角度计算像素取向，其中导丝像素具有比非最大滤波器响应幅度更大的权重， 引导线像素，以及对取向和权重进行下采样以计算第一图像的分辨率的一半的第二图像，其中下采样考虑分配给导丝像素的取向和较高权重。

    System and Method For Detecting An Object In A High Dimensional Space
    50.
    发明申请
    System and Method For Detecting An Object In A High Dimensional Space 有权
    用于在高维空间中检测对象的系统和方法

    公开(公告)号：US20080085050A1

    公开(公告)日：2008-04-10

    申请号：US11856208

    申请日：2007-09-17

    申请人： Adrian Barbu ,  Yefeng Zheng ,  Jing Yang ,  Bogdan Georgescu ,  Dorin Comaniciu

    发明人： Adrian Barbu ,  Yefeng Zheng ,  Jing Yang ,  Bogdan Georgescu ,  Dorin Comaniciu

    IPC分类号： G06K9/00

    CPC分类号： G06K9/6292

    摘要： A system and method for detecting an object in a high dimensional image space is disclosed. A three dimensional image of an object is received. A first classifier is trained in the marginal space of the object center location which generates a predetermined number of candidate object center locations. A second classifier is trained to identify potential object center locations and orientations from the predetermined number of candidate object center locations and maintaining a subset of the candidate object center locations. A third classifier is trained to identify potential locations, orientations and scale of the object center from the subset of the candidate object center locations. A single candidate object pose for the object is identified.

    摘要翻译： 公开了一种用于检测高维图像空间中的对象的系统和方法。 接收对象的三维图像。 在对象中心位置的边缘空间中训练第一分类器，其生成预定数量的候选对象中心位置。 训练第二分类器以从预定数量的候选对象中心位置识别潜在对象中心位置和方向，并维护候选对象中心位置的子集。 训练第三分类器以从候选对象中心位置的子集中识别对象中心的潜在位置，方向和尺度。 识别对象的单个候选对象姿势。