System and Method for Detecting Spherical and Ellipsoidal Objects Using Cutting Planes
    11.
    发明申请
    System and Method for Detecting Spherical and Ellipsoidal Objects Using Cutting Planes 审中-公开
    使用切割平面检测球形和椭圆体物体的系统和方法

    公开(公告)号:US20090016583A1

    公开(公告)日:2009-01-15

    申请号:US12169773

    申请日:2008-07-09

    IPC分类号: G06K9/46

    摘要: A method for detecting spherical and ellipsoidal objects is digitized medical images includes providing a 2-dimensional (2D) slice I(x, y) extracted from a medical image volume of a colon, said image volume comprising a plurality of intensities associated with a 3 grid of points, generating a plurality of templates of different sizes whose shape matches a target structure being sought in said slice, calculating a normalized gradient from said slice, calculating a diverging field gradient response (DFGR) for each of the plurality of masks with the normalized gradient, and selecting a strongest response as being indicative of the position and size of the target structure.

    摘要翻译: 用于检测球形和椭圆体的方法是数字化医学图像,包括提供从结肠的医学图像体积提取的二维(2D)切片I(x,y),所述图像体积包括与3 生成多个不同尺寸的模板,其形状与在所述切片中寻找的目标结构相匹配,从所述切片计算归一化梯度,计算多个掩模中的每一个的发散场梯度响应(DFGR) 并且选择最强的响应来表示目标结构的位置和大小。

    Method and system for polyp segmentation for 3D computed tomography colonography
    12.
    发明授权
    Method and system for polyp segmentation for 3D computed tomography colonography 有权
    用于3D计算机断层扫描结构的息肉分割方法和系统

    公开(公告)号:US08184888B2

    公开(公告)日:2012-05-22

    申请号:US12231772

    申请日:2008-09-05

    IPC分类号: G06K9/46

    摘要: A method and system for polyp segmentation in computed tomography colonogrphy (CTC) volumes is disclosed. The polyp segmentation method utilizes a three-staged probabilistic binary classification approach for automatically segmenting polyp voxels from surrounding tissue in CTC volumes. Based on an input initial polyp position, a polyp tip is detected in a CTC volume using a trained 3D point detector. A local polar coordinate system is then fit to the colon surface in the CTC volume with the origin at the detected polyp tip. Polyp interior voxels and polyp exterior voxels are detected along each axis of the local polar coordinate system using a trained 3D box. A boundary voxel is detected on each axis of the local polar coordinate system based on the detected polyp interior voxels and polyp exterior voxels by boosted 1D curve parsing using a trained classifier. This results in a segmented polyp boundary.

    摘要翻译: 公开了一种计算机断层扫描(CTC)体积中息肉分割的方法和系统。 息肉分割方法采用三阶段概率二分类方法,自动分割CTC体积周围组织的息肉体素。 基于输入的初始息肉位置,使用训练有素的3D点检测器在CTC体积中检测息肉末端。 然后将局部极坐标系拟合到CTC体积中的结肠表面,其中原点在检测到的息肉末端。 使用训练有素的3D框,在局部极坐标系的每个轴上检测Polyp内部体素和息肉外部体素。 基于检测到的息肉内部体素和息肉外部体素,通过使用训练有素的分类器进行升压1D曲线解析,在局部极坐标系的每个轴上检测边界体素。 这导致分段息肉边界。

    User interface for polyp annotation, segmentation, and measurement in 3D computed tomography colonography
    13.
    发明授权
    User interface for polyp annotation, segmentation, and measurement in 3D computed tomography colonography 有权
    用于三维计算机断层扫描结构中息肉注解,分割和测量的用户界面

    公开(公告)号:US08126244B2

    公开(公告)日:2012-02-28

    申请号:US12231771

    申请日:2008-09-05

    IPC分类号: G06K9/34

    摘要: A method and system for providing a user interface for polyp annotation, segmentation, and measurement in computer tomography colonography (CTC) volumes is disclosed. The interface receives an initial polyp position in a CTC volume, and automatically segments the polyp based on the initial polyp position. In order to segment the polyp, a polyp tip is detected in the CTC volume using a trained 3D point detector. A local polar coordinate system is then fit to the colon surface in the CTC volume with the origin at the detected polyp tip. Polyp interior voxels and polyp exterior voxels are detected along each axis of the local polar coordinate system using a trained 3D box. A boundary voxel is detected on each axis of the local polar coordinate system based on the detected polyp interior voxels and polyp exterior voxels by boosted 1D curve parsing using a trained classifier. This results in a segmented polyp boundary. The segmented polyp is displayed in the user interface, and a user can modify the segmented polyp boundary using the interface. The interface can measure the size of the segmented polyp in three dimensions. The user can also use the interface for polyp annotation in CTC volumes.

    摘要翻译: 公开了一种用于在计算机断层造影(CTC)体积中提供用于息肉注释,分割和测量的用户界面的方法和系统。 界面在CTC体积中接收初始息肉位置,并根据初始息肉位置自动分段息肉。 为了分割息肉,使用训练有素的3D点检测器在CTC体积中检测息肉末端。 然后将局部极坐标系拟合到CTC体积中的结肠表面,其中原点在检测到的息肉末端。 使用训练有素的3D框,在局部极坐标系的每个轴上检测Polyp内部体素和息肉外部体素。 基于检测到的息肉内部体素和息肉外部体素,通过使用训练有素的分类器进行升压1D曲线解析,在局部极坐标系的每个轴上检测边界体素。 这导致分段息肉边界。 分段息肉显示在用户界面中,用户可以使用界面修改分段息肉边界。 界面可以在三维中测量分段息肉的大小。 用户还可以在CTC卷中使用界面进行息肉注释。

    System and method for body extraction in medical image volumes
    16.
    发明授权
    System and method for body extraction in medical image volumes 有权
    医学图像体内体内提取的系统和方法

    公开(公告)号:US07650025B2

    公开(公告)日:2010-01-19

    申请号:US11493308

    申请日:2006-07-26

    IPC分类号: G06K9/00

    摘要: A method for identifying non-body structures in digitized medical images including the steps of providing a digitized image comprising a plurality of intensities corresponding to a domain of points on an N-dimensional grid, wherein said image includes a representation of a body and of non-body structures separate from said body, initializing a surface in said image on a side of said non-body structures opposite from said body, defining a plurality of forces acting on said surface, and displacing said surface through said non-body structures using said forces until said body is encountered.

    摘要翻译: 一种用于识别数字化医学图像中的非身体结构的方法,包括以下步骤:提供包括与N维网格上的点的区域相对应的多个强度的数字化图像,其中所述图像包括身体和非身体结构的表示, 与所述身体分开的身体结构,在与所述身体相对的所述非身体结构的一侧初始化所述图像中的表面,限定作用在所述表面上的多个力,并且使用所述身体结构使所述表面移位通过所述非身体结构 直到遇到身体。

    System and method for body extraction in medical image volumes
    17.
    发明申请
    System and method for body extraction in medical image volumes 有权
    医学图像体内体内提取的系统和方法

    公开(公告)号:US20070036411A1

    公开(公告)日:2007-02-15

    申请号:US11493308

    申请日:2006-07-26

    IPC分类号: G06K9/00

    摘要: A method for identifying non-body structures in digitized medical images including the steps of providing a digitized image comprising a plurality of intensities corresponding to a domain of points on an N-dimensional grid, wherein said image includes a representation of a body and of non-body structures separate from said body, initializing a surface in said image on a side of said non-body structures opposite from said body, defining a plurality of forces acting on said surface, and displacing said surface through said non-body structures using said forces until said body is encountered.

    摘要翻译: 一种用于识别数字化医学图像中的非身体结构的方法,包括以下步骤:提供包括对应于N维网格上的点的域的多个强度的数字化图像,其中所述图像包括身体和非身体结构的表示, 与所述身体分开的身体结构,在与所述身体相对的所述非身体结构的一侧初始化所述图像中的表面,限定作用在所述表面上的多个力,并且使用所述身体结构使所述表面移位通过所述非身体结构 直到遇到身体。

    System and method for determining compactness in images
    18.
    发明申请
    System and method for determining compactness in images 有权
    确定图像紧凑度的系统和方法

    公开(公告)号:US20050058349A1

    公开(公告)日:2005-03-17

    申请号:US10916808

    申请日:2004-08-12

    申请人: Matthias Wolf

    发明人: Matthias Wolf

    摘要: An image processing system for recognizing image features in three dimensional images, which can be medical images, uses a mask generator for generating masks that are used by a candidate searcher to search for candidate images in the three dimensional image. The candidate searcher applies the mask to a section of a foreground region of the image to determine the presence of a structure/object by counting the number of intersections between the mask and the section of the foreground region.

    摘要翻译: 用于识别可以是医学图像的三维图像中的图像特征的图像处理系统使用掩模生成器来生成由候选搜索器使用以在三维图像中搜索候选图像的掩模。 候选搜索器将掩模应用于图像的前景区域的一部分,以通过对掩模与前景区域的部分之间的交点数进行计数来确定结构/对象的存在。

    System and Method for Detecting Tagged Material Using Alpha Matting
    19.
    发明申请
    System and Method for Detecting Tagged Material Using Alpha Matting 有权
    使用Alpha Matting检测标签材料的系统和方法

    公开(公告)号:US20090097728A1

    公开(公告)日:2009-04-16

    申请号:US12244428

    申请日:2008-10-02

    IPC分类号: G06K9/00

    摘要: A method for computer-aided object classification, soft segmentation and layer extraction in computed tomographic colonography includes providing a contrast enhanced computed tomography (CT) digital image of the colon, finding a foreground region of voxels with an intensity higher than a pre-defined foreground threshold, creating a 3D trimap of the colon where the image is segmented into the foreground region, a background region, and an unknown region between the foreground and background, starting from the background, extracting successive layers of the unknown region until the foreground region is reached, and classifying each extracted layer as background or foreground, and generating a foreground matte, a background matte, and an alpha matte, where alpha indicates a mixing ration of foreground and background voxels.

    摘要翻译: 计算机辅助对象分类,计算机断层造影中的软分割和层提取的方法包括提供冒号的对比度增强计算机断层摄影(CT)数字图像,找到具有高于预定义前景的体素的前景区域 阈值,从背景开始,将图像分割成前景区域,背景区域和前景和背景之间的未知区域,从而提取未知区域的连续层,直到前景区域为 达到并将每个提取的层分类为背景或前景,并生成前景无光泽,背景无光泽和阿尔法无光泽,其中alpha表示前景和背景体素的混合比。

    System and Method for Robust Segmentation of Tubular Structures in 2D and 3D Images
    20.
    发明申请
    System and Method for Robust Segmentation of Tubular Structures in 2D and 3D Images 有权
    用于2D和3D图像中管状结构的鲁棒分割的系统和方法

    公开(公告)号:US20090041315A1

    公开(公告)日:2009-02-12

    申请号:US12183433

    申请日:2008-07-31

    IPC分类号: G06K9/00 G06K9/34

    摘要: A method for segmenting tubular structures in medical images includes providing at least a start point and an end point in a digital image volume, minimizing an action surface U0(p) which, at each image point p, corresponds to a minimal energy integrated along a path that starts at start point p0 and ends at p, sliding back on the minimal action surface from an end point to the start point to find a minimal path connecting the terminal points, initializing a level set function with points on the minimal path, and evolving the level set function to find a surface of a structure about the minimal path, wherein the level set function is constrained to be close to a signed distance function and wherein the level set function is prevented from growing wider than a predetermined diameter R, wherein the surface about the minimal path defines a tubular structure.

    摘要翻译: 用于在医学图像中分割管状结构的方法包括在数字图像体积中提供至少一个起始点和终点,从而最小化在每个图像点p处对应于沿着图像点集成的最小能量的作用表面U0(p) 从起始点p0开始并以p结束的路径,从终点到起始点在最小动作表面上滑回,以找到连接终点的最小路径,初始化最小路径上的点的级别集函数,以及 演化水平集函数以找到关于最小路径的结构的表面,其中水平设定函数被约束为接近有符号距离函数,并且其中防止水平集函数生长得比预定直径R更宽,其中 关于最小路径的表面限定了管状结构。