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    THREE DIMENSIONAL MODELING OF OBJECTS
    2.
    发明申请
    THREE DIMENSIONAL MODELING OF OBJECTS 审中-公开
    对象的三维建模

    公开(公告)号：US20080030497A1

    公开(公告)日：2008-02-07

    申请号：US11608750

    申请日：2006-12-08

    申请人： Yangqiu Hu ,  David Haynor ,  Randal Ching ,  Mark Ganter ,  William Ledoux ,  Duane Storti

    发明人： Yangqiu Hu ,  David Haynor ,  Randal Ching ,  Mark Ganter ,  William Ledoux ,  Duane Storti

    IPC分类号： G06T15/00

    CPC分类号： G06K9/342 ,  B33Y80/00 ,  G06T7/11 ,  G06T7/149 ,  G06T7/162 ,  G06T2200/04 ,  G06T2207/10072 ,  G06T2207/20072 ,  G06T2207/20101 ,  G06T2207/20161 ,  G06T2207/30008

    摘要： A method is disclosed for segmentation of three dimensional image data sets, to obtain digital models of objects identifiable in the image data set. The image data set may be obtained from any convenient source, including medical imaging modalities, geological imaging, industrial imaging, and the like. A graph cuts method is applied to the image data set, and a level set method is then applied to the data using the output from the graph cuts method. The graph cuts process comprises determining location information for the digital data on a 3D graph, and cutting the 3D graph to determine approximate membership information for the object. The boundaries of the object is then refined using the level set method. Finally, a representation of the object volumes can be derived from an output of the level set method. Such representation may be used to generate rapid prototyped physical models of the objects.

    摘要翻译： 公开了一种用于三维图像数据集的分割的方法，以获得在图像数据集中可识别的对象的数字模型。 图像数据集可以从任何方便的来源获得，包括医学成像模式，地质成像，工业成像等。 将图形切割方法应用于图像数据集，然后使用图形切割方法的输出将数据的级别设置方法应用于数据。 图形切割过程包括在3D图上确定数字数据的位置信息，以及切割3D图形以确定对象的近似成员资格信息。 然后使用级别集方法对对象的边界进行细化。 最后，可以从级别集方法的输出中导出对象卷的表示。 这种表示可以用于生成对象的快速原型物理模型。

    FUNCTION-BASED REPRESENTATION OF N-DIMENSIONAL STRUCTURES
    3.
    发明申请
    FUNCTION-BASED REPRESENTATION OF N-DIMENSIONAL STRUCTURES 有权
    基于功能的N维结构的表示

    公开(公告)号：US20120287129A1

    公开(公告)日：2012-11-15

    申请号：US13554978

    申请日：2012-07-20

    申请人： Duane Storti ,  Mark Ganter

    发明人： Duane Storti ,  Mark Ganter

    IPC分类号： G06T15/00

    CPC分类号： G06K9/342 ,  B33Y50/00 ,  G06T7/12 ,  G06T7/149 ,  G06T7/60 ,  G06T17/10 ,  G06T2200/04 ,  G06T2207/10072 ,  G06T2207/20016 ,  G06T2207/20044 ,  G06T2207/20064 ,  G06T2207/20161 ,  G06T2207/30004

    摘要： A method for modeling an object, particularly suited to complex objects such as anatomical objects, and manipulating the modeled object in a CAD environment includes obtaining volumetric scan data of a region and segmenting the scan data to identify a first object to produce a first set of signed distance values on a grid. Wavelet analysis of the first set of signed distance values provides a function-based representation of the object. A signed distance value model of a second object is obtained, and one or both sets of signed distance values are manipulated to perform a CAD operation.

    摘要翻译： 一种用于建模对象的方法，特别适用于诸如解剖学对象的复杂对象，以及在CAD环境中操纵所建模的对象，包括获取区域的体积扫描数据并分割扫描数据以识别第一对象以产生第一组 网格上的有符号距离值。 第一组有符号距离值的小波分析提供了对象的基于函数的表示。 获得第二物体的带符号距离值模型，并且操作一个或两组有符号距离值以执行CAD操作。

    SOLID MODELING BASED ON VOLUMETRIC SCANS
    4.
    发明申请
    SOLID MODELING BASED ON VOLUMETRIC SCANS 有权
    基于体积扫描的固体建模

    公开(公告)号：US20090244065A1

    公开(公告)日：2009-10-01

    申请号：US12433555

    申请日：2009-04-30

    申请人： Duane Storti ,  Mark Ganter

    发明人： Duane Storti ,  Mark Ganter

    IPC分类号： G06T17/00 ,  G06K9/00

    CPC分类号： G06K9/342 ,  B33Y50/00 ,  G06T7/12 ,  G06T7/149 ,  G06T7/60 ,  G06T17/10 ,  G06T2200/04 ,  G06T2207/10072 ,  G06T2207/20016 ,  G06T2207/20044 ,  G06T2207/20064 ,  G06T2207/20161 ,  G06T2207/30004

    摘要： The geometry of an object is inferred from values of the signed distance sampled on a uniform grid to efficiently model objects based on data derived from imaging technology that is now ubiquitous in medical diagnostics. Techniques for automated segmentation convert imaging intensity to a signed distance function (SDF), and a voxel structure imposes a uniform sampling grid. Essential properties of the SDF are used to construct upper and lower bounds on the allowed variation in signed distance in 1, 2, and 3 (or more) dimensions. The bounds are combined to produce interval-valued extensions of the SDF, including a tight global extension and more computationally efficient local bounds that provide useful criteria for root exclusion/isolation, enabling modeling of the objects and other applications.

    摘要翻译： 物体的几何结构是根据在均匀网格上采样的有符号距离的值推断的，以便根据现在医学诊断中无处不在的成像技术获得的数据有效地建模对象。 用于自动分割的技术将成像强度转换为带符号距离函数（SDF），并且体素结构施加均匀的采样网格。 SDF的基本属性用于在1,2和3（或更多）维度的带符号距离的允许变化上构建上限和下限。 组合边界以产生SDF的间隔值扩展，包括严格的全局扩展和更有计算效率的局部边界，为根排除/隔离提供有用的标准，从而实现对象和其他应用程序的建模。

    Solid modeling based on volumetric scans
    6.
    发明授权
    Solid modeling based on volumetric scans 有权
    基于体积扫描的实体建模

    公开(公告)号：US08401264B2

    公开(公告)日：2013-03-19

    申请号：US12433555

    申请日：2009-04-30

    申请人： Duane Storti ,  Mark Ganter

    发明人： Duane Storti ,  Mark Ganter

    IPC分类号： G06K9/00

    CPC分类号： G06K9/342 ,  B33Y50/00 ,  G06T7/12 ,  G06T7/149 ,  G06T7/60 ,  G06T17/10 ,  G06T2200/04 ,  G06T2207/10072 ,  G06T2207/20016 ,  G06T2207/20044 ,  G06T2207/20064 ,  G06T2207/20161 ,  G06T2207/30004

    摘要： The geometry of an object is inferred from values of the signed distance sampled on a uniform grid to efficiently model objects based on data derived from imaging technology that is now ubiquitous in medical diagnostics. Techniques for automated segmentation convert imaging intensity to a signed distance function (SDF), and a voxel structure imposes a uniform sampling grid. Essential properties of the SDF are used to construct upper and lower bounds on the allowed variation in signed distance in 1, 2, and 3 (or more) dimensions. The bounds are combined to produce interval-valued extensions of the SDF, including a tight global extension and more computationally efficient local bounds that provide useful criteria for root exclusion/isolation, enabling modeling of the objects and other applications.

    摘要翻译： 物体的几何结构是根据在均匀网格上采样的有符号距离的值推断的，以便根据现在医学诊断中无处不在的成像技术获得的数据有效地建模对象。 用于自动分割的技术将成像强度转换为带符号距离函数（SDF），并且体素结构施加均匀的采样网格。 SDF的基本属性用于在1,2和3（或更多）维度的带符号距离的允许变化上构建上限和下限。 组合边界以产生SDF的间隔值扩展，包括严格的全局扩展和更有计算效率的局部边界，为根排除/隔离提供有用的标准，从而实现对象和其他应用程序的建模。