利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

22 条记录 (耗时 0.022 秒)

    System and methods for image segmentation in n-dimensional space
    6.
    发明授权
    System and methods for image segmentation in n-dimensional space 有权
    在n维空间中图像分割的系统和方法

    公开(公告)号：US07995810B2

    公开(公告)日：2011-08-09

    申请号：US11474070

    申请日：2006-06-23

    申请人： Kang Li ,  Xiaodong Wu ,  Danny Z. Chen ,  Milan Sonka

    发明人： Kang Li ,  Xiaodong Wu ,  Danny Z. Chen ,  Milan Sonka

    IPC分类号： G06K9/00

    CPC分类号： G06K9/4638 ,  G06K9/6224 ,  G06T7/12 ,  G06T7/162 ,  G06T2207/10072 ,  G06T2207/20044 ,  G06T2207/30101

    摘要： A system and methods for the efficient segmentation of globally optimal surfaces representing object boundaries in volumetric datasets is provided. An optical surface detection system and methods are provided that are capable of simultaneously detecting multiple interacting surfaces in which the optimality is controlled by the cost functions designed for individual surfaces and by several geometric constraints defining the surface smoothness and interrelations.

    摘要翻译： 提供了一种用于在体数据集中表示对象边界的全局最优表面的有效分割的系统和方法。 提供了一种光学表面检测系统和方法，其能够同时检测多个相互作用的表面，其中最优性由为各个表面设计的成本函数以及限定表面平滑度和相互关系的若干几何约束来控制。

    System and methods for image segmentation in n-dimensional space
    7.
    发明申请
    System and methods for image segmentation in n-dimensional space 有权
    在n维空间中图像分割的系统和方法

    公开(公告)号：US20070058865A1

    公开(公告)日：2007-03-15

    申请号：US11474070

    申请日：2006-06-23

    申请人： Kang Li ,  Xiaodong Wu ,  Danny Chen ,  Milan Sonka

    发明人： Kang Li ,  Xiaodong Wu ,  Danny Chen ,  Milan Sonka

    IPC分类号： G06K9/34 ,  G06K9/62

    CPC分类号： G06K9/4638 ,  G06K9/6224 ,  G06T7/12 ,  G06T7/162 ,  G06T2207/10072 ,  G06T2207/20044 ,  G06T2207/30101

    摘要： A system and methods for the efficient segmentation of globally optimal surfaces representing object boundaries in volumetric datasets is provided. An optical surface detection system and methods are provided that are capable of simultaneously detecting multiple interacting surfaces in which the optimality is controlled by the cost functions designed for individual surfaces and by several geometric constraints defining the surface smoothness and interrelations.

    摘要翻译： 提供了一种用于在体数据集中表示对象边界的全局最优表面的有效分割的系统和方法。 提供了一种光学表面检测系统和方法，其能够同时检测多个相互作用的表面，其中最优性由为各个表面设计的成本函数以及限定表面平滑度和相互关系的若干几何约束来控制。

    Method and apparatus for analyzing CT images to determine the presence of pulmonary tissue pathology
    8.
    发明授权
    Method and apparatus for analyzing CT images to determine the presence of pulmonary tissue pathology 失效
    用于分析CT图像以确定肺组织病理学存在的方法和装置

    公开(公告)号：US06466687B1

    公开(公告)日：2002-10-15

    申请号：US09022093

    申请日：1998-02-11

    申请人： Renuka Uppaluri ,  Theophano Mitsa ,  Eric A. Hoffman ,  Geoffrey McLennan ,  Milan Sonka

    发明人： Renuka Uppaluri ,  Theophano Mitsa ,  Eric A. Hoffman ,  Geoffrey McLennan ,  Milan Sonka

    IPC分类号： G06K900

    CPC分类号： G06T7/0012

    摘要： A method and apparatus for analyzing CT images to determine the presence of pulmonary tissue pathology, such as in emphysema, IPF, sarcoid, etc. In accordance with one embodiment, a CT slice is selected to perform an automated, objective, and quantitative analysis of the slice. Initially, an image processing stage is performed, which includes segmentation and edgementation of the selected CT slice for preparation of a series of objective, quantitative measures to be performed on the slice. A region of interest (ROI) is selected on the CT slice in which these objective, quatitative measures are to be taken. The first set of objective, quantitative measures are first order texture measures that describe a frequency of occurrence of all gray levels assigned to pixels within the ROI of the image slice. The second set of objective, quantitative measures are second order texture measures that characterize the spatial interdependencies between particular pixels of the ROI. Fractal analysis could also be performed to provide additional objective, quantitative measures of the ROI. The ROI is classified to a particular tissue pathology class based upon an optimal subset of first or second order texture measures and fractal measures obtained. A color-coded output is displayed for visual presentation to a user indicating the different tissue pathology classes assigned to different regions of the CT slice.

    摘要翻译： 用于分析CT图像以确定肺组织病理学的存在的方法和装置，例如在肺气肿，IPF，结节样等中。根据一个实施例，选择CT切片以执行自动化，客观和定量分析 切片。 最初，执行图像处理阶段，其包括所选择的CT切片的分割和分割，以准备在切片上执行的一系列客观的定量测量。 在CT切片上选择感兴趣区域（ROI），在这些切片中将采用这些客观的定量测量方法。 第一组客观量化措施是描述分配给图像切片ROI内的像素的所有灰度级发生频率的一阶纹理度量。 第二组客观的量化措施是表征ROI的特定像素之间的空间相互依赖性的二阶纹理度量。 还可以进行分形分析，以提供投资回报率的额外目标，定量测量。 基于获得的一阶或二阶纹理测量和分形测量的最佳子集，将ROI归类为特定的组织病理学类别。 显示颜色编码的输出，用于向用户呈现指示分配给CT切片的不同区域的不同组织病理学类别的用户。