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公开(公告)号：US09460510B2
公开(公告)日：2016-10-04
申请号：US13853174
申请日：2013-03-29
申请人： Gerardo Hermosillo Valadez , Marcos Salganicoff , Matthias Wolf , Xiang Sean Zhou , Yiqiang Zhan
发明人： Gerardo Hermosillo Valadez , Marcos Salganicoff , Matthias Wolf , Xiang Sean Zhou , Yiqiang Zhan
CPC分类号： G06T7/0028 , G06T7/33 , G06T2207/30004
摘要： Disclosed herein is a framework for facilitating synchronized image navigation. In accordance with one aspect, at least first and second medical images are received. A non-linear mapping between the first and second medical images is generated. A selection of a given location in the first medical image is received in response to a user's navigational operation. Without deforming the second medical image, a target location in the second medical image is determined by using the non-linear mapping. The target location corresponds to the given location in the first medical image. An optimized deformation-free view of the second medical image is generated based at least in part on the target location. While the user performs navigational operations on the first medical image, the framework repeatedly receives the selection of the given location, determines the target location using the non-linear mapping, and generates the optimized deformation-free view of the second medical image based at least in part on the target location.
摘要翻译： 这里公开了一种促进同步图像导航的框架。 根据一个方面，至少接收第一和第二医学图像。 产生第一和第二医学图像之间的非线性映射。 响应于用户的导航操作接收对第一医疗图像中的给定位置的选择。 在不使第二医用图像变形的情况下，通过使用非线性映射来确定第二医用图像中的目标位置。 目标位置对应于第一医疗图像中的给定位置。 至少部分地基于目标位置产生第二医疗图像的优化的无变形视图。 当用户在第一医学图像上执行导航操作时，框架重复地接收对给定位置的选择，使用非线性映射确定目标位置，并且至少基于第二医学图像生成优化的无变形视图 部分在目标位置。
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公开(公告)号：US20140294263A1
公开(公告)日：2014-10-02
申请号：US13853174
申请日：2013-03-29
申请人： Gerardo Hermosillo Valadez , Marcos Salganicoff , Matthias Wolf , Xiang Sean Zhou , Yiqiang Zhan
发明人： Gerardo Hermosillo Valadez , Marcos Salganicoff , Matthias Wolf , Xiang Sean Zhou , Yiqiang Zhan
IPC分类号： G06T7/00
CPC分类号： G06T7/0028 , G06T7/33 , G06T2207/30004
摘要： Disclosed herein is a framework for facilitating synchronized image navigation. In accordance with one aspect, at least first and second medical images are received. A non-linear mapping between the first and second medical images is generated. A selection of a given location in the first medical image is received in response to a user's navigational operation. Without deforming the second medical image, a target location in the second medical image is determined by using the non-linear mapping. The target location corresponds to the given location in the first medical image. An optimized deformation-free view of the second medical image is generated based at least in part on the target location. While the user performs navigational operations on the first medical image, the framework repeatedly receives the selection of the given location, determines the target location using the non-linear mapping, and generates the optimized deformation-free view of the second medical image based at least in part on the target location.
摘要翻译： 这里公开了一种促进同步图像导航的框架。 根据一个方面，至少接收第一和第二医学图像。 产生第一和第二医学图像之间的非线性映射。 响应于用户的导航操作接收对第一医疗图像中的给定位置的选择。 在不使第二医用图像变形的情况下，通过使用非线性映射来确定第二医用图像中的目标位置。 目标位置对应于第一医疗图像中的给定位置。 至少部分地基于目标位置产生第二医疗图像的优化的无变形视图。 当用户在第一医学图像上执行导航操作时，框架重复地接收对给定位置的选择，使用非线性映射确定目标位置，并且至少基于第二医学图像生成优化的无变形视图 部分在目标位置。
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公开(公告)号：US20140161337A1
公开(公告)日：2014-06-12
申请号：US14096206
申请日：2013-12-04
申请人： Vikas C. Raykar , Yiqiang Zhan , Maneesh Dewan , Gerardo Hermosillo Valadez , Zhigang Peng , Xiang Sean Zhou
发明人： Vikas C. Raykar , Yiqiang Zhan , Maneesh Dewan , Gerardo Hermosillo Valadez , Zhigang Peng , Xiang Sean Zhou
CPC分类号： G06K9/6202 , G06K9/6211 , G06K9/629 , G06T7/33 , G06T2207/10072 , G06T2207/30016 , G06T2207/30096
摘要： Disclosed herein is a framework for facilitating adaptive anatomical region prediction. In accordance with one aspect, a set of exemplar images including annotated first landmarks is received. User definitions of first anatomical regions in the exemplar images are obtained. The framework may detect second landmarks in a subject image. It may further compute anatomical similarity scores between the subject image and the exemplar images based on the first and second landmarks, and predict a second anatomical region in the subject image by adaptively combining the first anatomical regions based on the anatomical similarity scores.
摘要翻译： 本文公开了一种用于促进适应性解剖区域预测的框架。 根据一个方面，接收包括注释的第一地标的一组示例图像。 获得示例图像中的第一解剖区域的用户定义。 框架可以检测主题图像中的第二地标。 它还可以基于第一和第二界标进一步计算对象图像和样本图像之间的解剖学相似性得分，并且基于解剖学相似性得分来自适应地组合第一解剖区域来预测对象图像中的第二解剖区域。
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公开(公告)号：US09020235B2
公开(公告)日：2015-04-28
申请号：US13363753
申请日：2012-02-01
申请人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
发明人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
CPC分类号： A61B6/5217 , A61B5/055 , A61B5/4504 , A61B5/726 , A61B5/7425 , A61B5/743 , A61B5/7485 , A61B6/032 , A61B6/469 , A61B6/505 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T2207/10116
摘要： Systems and methods for supporting a diagnostic workflow from a computer system are disclosed herein. In accordance with one implementation, a set of pre-identified anatomical landmarks associated with one or more structures of interest within one or more medical images are presented to a user. In response to a user input selecting at least one or more regions of interest including one or more of the pre-identified anatomical landmarks, the user is automatically navigated to the selected region of interest. In another implementation, a second user input selecting one or more measurement tools is received. An evaluation may be automatically determined based on one or more of the set of anatomical landmarks in response to the second user input.
摘要翻译： 本文公开了用于从计算机系统支持诊断工作流程的系统和方法。 根据一个实施方案，向用户呈现与一个或多个医学图像内的一个或多个感兴趣结构相关联的一组预先识别的解剖学标记。 响应于用户输入选择至少一个或多个感兴趣区域，包括预先识别的解剖标志中的一个或多个，用户被自动导航到所选择的感兴趣区域。 在另一实现中，接收选择一个或多个测量工具的第二用户输入。 响应于第二用户输入，可以基于该组解剖标志中的一个或多个来自动确定评估。
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公开(公告)号：US20120172700A1
公开(公告)日：2012-07-05
申请号：US13363753
申请日：2012-02-01
申请人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
发明人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
CPC分类号： A61B6/5217 , A61B5/055 , A61B5/4504 , A61B5/726 , A61B5/7425 , A61B5/743 , A61B5/7485 , A61B6/032 , A61B6/469 , A61B6/505 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T2207/10116
摘要： Systems and methods for supporting a diagnostic workflow from a computer system are disclosed herein. In accordance with one implementation, a set of pre-identified anatomical landmarks associated with one or more structures of interest within one or more medical images are presented to a user. In response to a user input selecting at least one or more regions of interest including one or more of the pre-identified anatomical landmarks, the user is automatically navigated to the selected region of interest. In another implementation, a second user input selecting one or more measurement tools is received. An evaluation may be automatically determined based on one or more of the set of anatomical landmarks in response to the second user input.
摘要翻译： 本文公开了用于从计算机系统支持诊断工作流程的系统和方法。 根据一个实施方案，向用户呈现与一个或多个医学图像内的一个或多个感兴趣结构相关联的一组预先识别的解剖学标记。 响应于用户输入选择至少一个或多个感兴趣区域，包括预先识别的解剖标志中的一个或多个，用户被自动导航到所选择的感兴趣区域。 在另一实现中，接收选择一个或多个测量工具的第二用户输入。 响应于第二用户输入，可以基于该组解剖标志中的一个或多个来自动确定评估。
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公开(公告)号：US09336457B2
公开(公告)日：2016-05-10
申请号：US14096206
申请日：2013-12-04
申请人： Vikas C. Raykar , Yiqiang Zhan , Maneesh Dewan , Gerardo Hermosillo Valadez , Zhigang Peng , Xiang Sean Zhou
发明人： Vikas C. Raykar , Yiqiang Zhan , Maneesh Dewan , Gerardo Hermosillo Valadez , Zhigang Peng , Xiang Sean Zhou
CPC分类号： G06K9/6202 , G06K9/6211 , G06K9/629 , G06T7/33 , G06T2207/10072 , G06T2207/30016 , G06T2207/30096
摘要： Disclosed herein is a framework for facilitating adaptive anatomical region prediction. In accordance with one aspect, a set of exemplar images including annotated first landmarks is received. User definitions of first anatomical regions in the exemplar images are obtained. The framework may detect second landmarks in a subject image. It may further compute anatomical similarity scores between the subject image and the exemplar images based on the first and second landmarks, and predict a second anatomical region in the subject image by adaptively combining the first anatomical regions based on the anatomical similarity scores.
摘要翻译： 本文公开了一种用于促进适应性解剖区域预测的框架。 根据一个方面，接收包括注释的第一地标的一组示例图像。 获得示例图像中的第一解剖区域的用户定义。 框架可以检测主题图像中的第二地标。 它还可以基于第一和第二界标进一步计算对象图像和样本图像之间的解剖学相似性得分，并且基于解剖学相似性得分来自适应地组合第一解剖区域来预测对象图像中的第二解剖区域。
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公开(公告)号：US08331699B2
公开(公告)日：2012-12-11
申请号：US12887640
申请日：2010-09-22
CPC分类号： G06K9/6219 , G06K9/6209 , G06K2209/051
摘要： Described herein is a framework for constructing a hierarchical classifier for facilitating classification of digitized data. In one implementation, a divergence measure of a node of the hierarchical classifier is determined. Data at the node is divided into at least two child nodes based on a splitting criterion to form at least a portion of the hierarchical classifier. The splitting criterion is selected based on the divergence measure. If the divergence measure is less than a predetermined threshold value, the splitting criterion comprises a divergence-based splitting criterion which maximizes subsequent divergence after a split. Otherwise, the splitting criterion comprises an information-based splitting criterion which seeks to minimize subsequent misclassification error after the split.
摘要翻译： 这里描述了用于构建用于促进数字化数据的分类的分级分类器的框架。 在一个实现中，确定分级分类器的节点的发散度量度。 基于分割标准将节点处的数据划分为至少两个子节点，以形成分级分类器的至少一部分。 基于分歧度量选择分割标准。 如果发散度小于预定阈值，则分割标准包括基于发散的分裂标准，其使分裂后的随后发散最大化。 否则，分割标准包括基于信息的分割标准，其寻求在分裂之后使随后的错误分类错误最小化。
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公开(公告)号：US09064332B2
公开(公告)日：2015-06-23
申请号：US14017344
申请日：2013-09-04
CPC分类号： G06T11/003 , G06T7/0014 , G06T2207/30008
摘要： Disclosed herein is a framework for facilitating fused-image visualization for surgery evaluation. In accordance with one aspect of the framework, at least one pre-operative image and at least one intra-operative image of an anatomical structure are received. A region of interest may be identified in the intra-operative image. The pre-operative image may be straightened, and a symmetric region may be identified in the straightened pre-operative image. The symmetric region is substantially symmetrical to a target region in the straightened pre-operative region. The target region corresponds to the region of interest in the intra-operative image. The symmetric region may be extracted and reflected to generate a reference image. The intra-operative image may be rigidly registered with the reference image to generate registered intra-operative image, which is overlaid on the target region in the straightened pre-operative image to generate a fused image.
摘要翻译： 本文公开了用于促进用于手术评估的融合图像可视化的框架。 根据框架的一个方面，接收解剖结构的至少一个术前图像和至少一个手术内图像。 可以在手术中的图像中识别感兴趣的区域。 可以矫正术前图像，并且可以在矫正的手术前图像中识别对称区域。 对称区域基本对称于矫正术前区域中的目标区域。 目标区域对应于手术中图像中的感兴趣区域。 对称区域可以被提取和反射以产生参考图像。 可以将手术内图像与参考图像刚性地注册，以产生注册的手术中图像，其被覆盖在矫正的术前图像中的目标区域上以产生融合图像。
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公开(公告)号：US20110044534A1
公开(公告)日：2011-02-24
申请号：US12887640
申请日：2010-09-22
IPC分类号： G06K9/62
CPC分类号： G06K9/6219 , G06K9/6209 , G06K2209/051
摘要： Described herein is a framework for constructing a hierarchical classifier for facilitating classification of digitized data. In one implementation, a divergence measure of a node of the hierarchical classifier is determined. Data at the node is divided into at least two child nodes based on a splitting criterion to form at least a portion of the hierarchical classifier. The splitting criterion is selected based on the divergence measure. If the divergence measure is less than a predetermined threshold value, the splitting criterion comprises a divergence-based splitting criterion which maximizes subsequent divergence after a split. Otherwise, the splitting criterion comprises an information-based splitting criterion which seeks to minimize subsequent misclassification error after the split.
摘要翻译： 这里描述了用于构建用于促进数字化数据的分类的分级分类器的框架。 在一个实现中，确定分级分类器的节点的发散度量度。 基于分割标准将节点处的数据划分为至少两个子节点，以形成分级分类器的至少一部分。 基于分歧度量选择分割标准。 如果发散度小于预定阈值，则分割标准包括基于发散的分裂标准，其使分裂后的随后发散最大化。 否则，分割标准包括基于信息的分割标准，其寻求在分裂之后使随后的错误分类错误最小化。
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公开(公告)号：US09082231B2
公开(公告)日：2015-07-14
申请号：US13737987
申请日：2013-01-10
CPC分类号： G06T11/60 , G06T3/0068 , G06T7/0014 , G06T11/00 , G06T2200/24 , G06T2207/10072 , G06T2207/10116 , G06T2207/10136 , G06T2207/30004
摘要： Disclosed herein is a framework for facilitating symmetry-based visualization. In accordance with one aspect of the framework, one or more medical images are received. The medical images include first and second regions, wherein the first region is substantially symmetric to the second region. A transformation is performed on at least the second region to generate a transformed second region. The transformed second region is registered with the first region to generate an aligned second region. The aligned second region and the first region are then alternately displayed to assist anomaly detection.
摘要翻译： 这里公开的是用于促进基于对称的可视化的框架。 根据框架的一个方面，接收一个或多个医学图像。 医学图像包括第一和第二区域，其中第一区域与第二区域基本对称。 至少在第二区域进行变换以产生变换的第二区域。 变换的第二区域与第一区域对齐以产生对准的第二区域。 然后交替地显示排列的第二区域和第一区域以辅助异常检测。
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