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    Image Registration
    2.
    发明申请
    Image Registration 有权
    图像注册

    公开(公告)号：US20120207359A1

    公开(公告)日：2012-08-16

    申请号：US13025500

    申请日：2011-02-11

    申请人： Ender Konukoglu ,  Sayan Pathak ,  Khan Mohammad Siddiqui ,  Antonio Criminisi ,  Steven White ,  Jamie Daniel Joseph Shotton ,  Duncan Paul Robertson

    发明人： Ender Konukoglu ,  Sayan Pathak ,  Khan Mohammad Siddiqui ,  Antonio Criminisi ,  Steven White ,  Jamie Daniel Joseph Shotton ,  Duncan Paul Robertson

    IPC分类号： G06K9/00 ,  G06K9/32

    CPC分类号： G06K9/6277 ,  G06K9/6282 ,  G06T7/35 ,  G06T2207/10072 ,  G06T2207/10116 ,  G06T2207/10132 ,  G06T2207/20072 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30004

    摘要： Image registration is described. In an embodiment an image registration system executes automatic registration of images, for example medical images. In an example, semantic information is computed for each of the images to be registered comprising information about the types of objects in the images and the certainty of that information. In an example a mapping is found to register the images which takes into account the intensities of the image elements as well as the semantic information in a manner which is weighted by the certainty of that semantic information. For example, the semantic information is computed by estimating posterior distributions for the locations of anatomical structures by using a regression forest and transforming the posterior distributions into a probability map. In an example the mapping is found as a global point of inflection of an energy function, the energy function having a term related to the semantic information.

    摘要翻译： 描述图像注册。 在一个实施例中，图像注册系统执行图像的自动注册，例如医学图像。 在一个示例中，为要注册的每个图像计算语义信息，包括关于图像中的对象的类型和该信息的确定性的信息。 在一个示例中，发现映射以以该语义信息的确定性加权的方式注册考虑了图像元素的强度以及语义信息的图像。 例如，通过使用回归森林估计解剖结构的位置的后验分布并将后验分布变换为概率图来计算语义信息。 在一个示例中，映射被发现为能量函数的拐点的全局点，能量函数具有与语义信息相关的术语。

    Automatic organ localization
    4.
    发明授权
    Automatic organ localization 有权
    自动器官定位

    公开(公告)号：US08867802B2

    公开(公告)日：2014-10-21

    申请号：US13090108

    申请日：2011-04-19

    申请人： Antonio Criminisi ,  Jamie Daniel Joseph Shotton ,  Duncan Paul Robertson ,  Sayan D. Pathak ,  Steven James White ,  Khan Mohammed Siddiqui

    发明人： Antonio Criminisi ,  Jamie Daniel Joseph Shotton ,  Duncan Paul Robertson ,  Sayan D. Pathak ,  Steven James White ,  Khan Mohammed Siddiqui

    IPC分类号： G06K9/00 ,  G06T7/00

    CPC分类号： G06T7/0048 ,  G06K2209/051 ,  G06T7/77 ,  G06T2207/10072 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30004

    摘要： Automatic organ localization is described. In an example, an organ in a medical image is localized using one or more trained regression trees. Each image element of the medical image is applied to the trained regression trees to compute probability distributions that relate to a distance from each image element to the organ. At least a subset of the probability distributions are selected and aggregated to calculate a localization estimate for the organ. In another example, the regression trees are trained using training images having a predefined organ location. At each node of the tree, test parameters are generated that determine which subsequent node each training image element is passed to. This is repeated until each image element reaches a leaf node of the tree. A probability distribution is generated and stored at each leaf node, based on the distance from the leaf node's image elements to the organ.

    摘要翻译： 描述自动器官定位。 在一个示例中，使用一个或多个经过训练的回归树将医学图像中的器官定位。 将医学图像的每个图像元素应用于经过训练的回归树，以计算与从每个图像元素到器官的距离相关的概率分布。 选择和聚合概率分布的至少一个子集以计算器官的定位估计。 在另一示例中，使用具有预定义的器官位置的训练图像来训练回归树。 在树的每个节点，生成测试参数，确定每个训练图像元素传递到哪个后续节点。 这是重复的，直到每个图像元素到达树的叶节点。 基于从叶节点的图像元素到器官的距离，在每个叶节点处生成并存储概率分布。

    System and method for image processing and generating a body model
    5.
    发明授权
    System and method for image processing and generating a body model 有权
    用于图像处理和生成人体模型的系统和方法

    公开(公告)号：US08605148B2

    公开(公告)日：2013-12-10

    申请号：US12881861

    申请日：2010-09-14

    申请人： Duncan Paul Robertson

    发明人： Duncan Paul Robertson

    IPC分类号： H04N7/18

    CPC分类号： G06T11/60 ,  F21V33/00 ,  G06T7/11 ,  G06T7/194 ,  G06T2207/30196 ,  G06T2210/16 ,  H04N5/2621 ,  H04N5/275 ,  H04N2005/2726

    摘要： Images of foreground objects in a scene are generated by causing electromagnetic radiation to be emitted having a first spectral power distribution from a surface of a first foreground object, which is adjacent or at least partially obscured by a second foreground object. A first image of both of the first and second foreground objects is acquired while the first foreground object emits electromagnetic radiation with the first spectral power distribution. A second image of the first and second foreground objects is acquired while the first foreground object is not emitting electromagnetic radiation or is emitting electromagnetic radiation with a second spectral power distribution which is different to the first spectral power distribution. An alpha matte of the first and second foreground objects is generated based on a comparison of the first image and second image.

    摘要翻译： 通过使第一前景物体的表面具有第一光谱功率分布而发射电磁辐射而产生场景中的前景物体的图像，第一前景物体的表面与第二前景物体相邻或至少部分地遮蔽。 当第一前景物体发射具有第一光谱功率分布的电磁辐射时，获取第一和第二前景物体的第一图像。 当第一前景物体不发射电磁辐射或正在发射具有与第一光谱功率分布不同的第二光谱功率分布的电磁辐射时，获取第一和第二前景物体的第二图像。 基于第一图像和第二图像的比较来生成第一和第二前景对象的阿尔法无光泽。