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1.发明申请SYSTEM AND METHOD FOR AUTOMATIC RECOGNITION AND LABELING OF ANATOMICAL STRUCTURES AND VESSELS IN MEDICAL IMAGING SCANS 有权医学成像扫描仪中自动识别和解剖结构与血管标签的系统与方法公开(公告)号：US20100054525A1
公开(公告)日：2010-03-04
申请号：US12199073
申请日：2008-08-27
IPC分类号： G06K9/62
CPC分类号： G06K9/6206 , G06K2209/05 , G06T7/11 , G06T7/149 , G06T7/187 , G06T2207/30012 , G06T2207/30101
摘要： A system and method for recognizing and labeling anatomical structures in an image includes creating a list of objects such that one or more objects on the list appear before a target object and setting the image as a context for a first object on the list. The first object is detected and labeled by subtracting a background of the image. A local context is set for a next object on the list using the first object. The next object is detected and labeled by registration using the local context. Setting a local context and detecting and labeling the next object are repeated until the target object is detected and labeled. Labeling of the target object is refined using region growing.
摘要翻译： 用于识别和标记图像中的解剖结构的系统和方法包括创建对象的列表，使得列表上的一个或多个对象出现在目标对象之前并且将图像设置为列表中的第一对象的上下文。 通过减去图像的背景来检测和标记第一个对象。 使用第一个对象为列表上的下一个对象设置本地上下文。 通过使用本地上下文的注册来检测和标记下一个对象。 重复设置本地上下文并检测和标记下一个对象，直到检测到目标对象并标记为止。 目标对象的标注使用区域增长进行细化。
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公开(公告)号：US20100014722A1
公开(公告)日：2010-01-21
申请号：US12176802
申请日：2008-07-21
IPC分类号： G06K9/00
CPC分类号： G06K9/6207 , G06K2209/05 , G06T7/11 , G06T7/35 , G06T2207/10081 , G06T2207/20128 , G06T2207/30004
摘要： A method for optimizing images, the method comprising, receiving a designation of a first feature of interest, receiving a designation of a second feature of interest, receiving a target image, receiving an atlas image including labels of first and second features of interest of the target image and a first optimization parameter associated with the first feature of interest and a second optimization parameter associated with the second feature of interest, mapping the atlas image onto the target image resulting in a global mapped image, defining an area of the first feature of interest and an area of the second feature of interest, mapping the reference image onto the area of the first feature of interest on the global mapped image using the first optimization parameter, and mapping the reference image onto the area of the second feature of interest on the global mapped image using the second optimization parameter.
摘要翻译： 一种用于优化图像的方法，所述方法包括：接收感兴趣的第一特征的指定，接收感兴趣的第二特征的指定，接收目标图像，接收包括所述感兴趣的第一和第二特征标记的图集图像 目标图像和与所述感兴趣的第一特征相关联的第一优化参数和与所述感兴趣的所述第二特征相关联的第二优化参数，将所述图集图像映射到所述目标图像上，导致全局映射图像，所述全局映射图像定义所述第一特征的区域 兴趣和感兴趣的第二特征的区域，使用第一优化参数在全局映射图像上将参考图像映射到感兴趣的第一特征的区域上，并将参考图像映射到感兴趣的第二特征的区域上 全局映射图像使用第二优化参数。
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3.发明授权System and method for automatic recognition and labeling of anatomical structures and vessels in medical imaging scans 有权用于医学影像扫描中解剖结构和血管的自动识别和标记的系统和方法公开(公告)号：US08385688B2
公开(公告)日：2013-02-26
申请号：US12199073
申请日：2008-08-27
CPC分类号： G06K9/6206 , G06K2209/05 , G06T7/11 , G06T7/149 , G06T7/187 , G06T2207/30012 , G06T2207/30101
摘要： A system and method for recognizing and labeling anatomical structures in an image includes creating a list of objects such that one or more objects on the list appear before a target object and setting the image as a context for a first object on the list. The first object is detected and labeled by subtracting a background of the image. A local context is set for a next object on the list using the first object. The next object is detected and labeled by registration using the local context. Setting a local context and detecting and labeling the next object are repeated until the target object is detected and labeled. Labeling of the target object is refined using region growing.
摘要翻译： 用于识别和标记图像中的解剖结构的系统和方法包括创建对象的列表，使得列表上的一个或多个对象出现在目标对象之前并且将图像设置为列表中的第一对象的上下文。 通过减去图像的背景来检测和标记第一个对象。 使用第一个对象为列表上的下一个对象设置本地上下文。 通过使用本地上下文的注册来检测和标记下一个对象。 重复设置本地上下文并检测和标记下一个对象，直到检测到目标对象并标记为止。 目标对象的标注使用区域增长进行细化。
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4.发明申请SYSTEM AND METHOD FOR AUTOMATIC RECOGNITION AND LABELING OF ANATOMICAL STRUCTURES AND VESSELS IN MEDICAL IMAGING SCANS 有权医学成像扫描仪中自动识别和解剖结构与血管标签的系统与方法公开(公告)号：US20120281904A1
公开(公告)日：2012-11-08
申请号：US13552160
申请日：2012-07-18
CPC分类号： G06K9/6206 , G06K2209/05 , G06T7/11 , G06T7/149 , G06T7/187 , G06T2207/30012 , G06T2207/30101
摘要： A system and method for recognizing and labeling anatomical structures in an image includes creating a list of objects such that one or more objects on the list appear before a target object and setting the image as a context for a first object on the list. The first object is detected and labeled by subtracting a background of the image. A local context is set for a next object on the list using the first object. The next object is detected and labeled by registration using the local context. Setting a local context and detecting and labeling the next object are repeated until the target object is detected and labeled. Labeling of the target object is refined using region growing.
摘要翻译： 用于识别和标记图像中的解剖结构的系统和方法包括创建对象的列表，使得列表上的一个或多个对象出现在目标对象之前并且将图像设置为列表中的第一对象的上下文。 通过减去图像的背景来检测和标记第一个对象。 使用第一个对象为列表上的下一个对象设置本地上下文。 通过使用本地上下文的注册来检测和标记下一个对象。 重复设置本地上下文并检测和标记下一个对象，直到检测到目标对象并标记为止。 目标对象的标注使用区域增长进行细化。
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公开(公告)号：US08244008B2
公开(公告)日：2012-08-14
申请号：US12176802
申请日：2008-07-21
IPC分类号： G06K9/00
CPC分类号： G06K9/6207 , G06K2209/05 , G06T7/11 , G06T7/35 , G06T2207/10081 , G06T2207/20128 , G06T2207/30004
摘要： A method for optimizing images, the method comprising, receiving a designation of a first feature of interest, receiving a designation of a second feature of interest, receiving a target image, receiving an atlas image including labels of first and second features of interest of the target image and a first optimization parameter associated with the first feature of interest and a second optimization parameter associated with the second feature of interest, mapping the atlas image onto the target image resulting in a global mapped image, defining an area of the first feature of interest and an area of the second feature of interest, mapping the reference image onto the area of the first feature of interest on the global mapped image using the first optimization parameter, and mapping the reference image onto the area of the second feature of interest on the global mapped image using the second optimization parameter.
摘要翻译： 一种用于优化图像的方法，所述方法包括：接收感兴趣的第一特征的指定，接收感兴趣的第二特征的指定，接收目标图像，接收包括所述感兴趣的第一和第二特征标记的图集图像 目标图像和与所述感兴趣的第一特征相关联的第一优化参数和与所述感兴趣的所述第二特征相关联的第二优化参数，将所述图集图像映射到所述目标图像上，导致全局映射图像，所述全局映射图像定义所述第一特征的区域 兴趣和感兴趣的第二特征的区域，使用第一优化参数在全局映射图像上将参考图像映射到感兴趣的第一特征的区域上，并将参考图像映射到感兴趣的第二特征的区域上 全局映射图像使用第二优化参数。
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6.发明申请METHOD AND KNOWLEDGE STRUCTURES FOR REASONING ABOUT CONCEPTS, RELATIONS, AND RULES 有权关于概念，关系和规则的方法和知识结构公开(公告)号：US20090055342A1
公开(公告)日：2009-02-26
申请号：US12261541
申请日：2008-10-30
CPC分类号： G06N5/04 , Y10S707/99935
摘要： A system and method for reasoning about concepts, relations and rules having a semantic network comprising at least one node from a predetermined set of node types, at least one link from a predetermined set of link types, and zero or more rules from a predetermined set of rule types, a subset of the rule types being matching rule types, each node and each link being associated with a set of zero or more rules; a network reasoning data structure having a reasoning type database having at least one regular expression, each of the regular expressions being a class of sequences having at least three node types and two link types, wherein the network reasoning data structure further has a context being a set of rules; and a reasoning engine having an activator for activating one or more activated paths in the semantic network, the set of activated paths having a common starting node in the semantic network, wherein the reasoning engine further has a validator for selecting a subset of the activated paths being valid paths, each rule from the set of rule matching types that is associated with one or more path elements on each valid path being matched by one or more rules in the context and wherein the reasoning engine further has a legal inferencer for selecting a subset of the set of valid paths being legal and valid paths, the legal and valid paths matching at least one of the regular expressions.
摘要翻译： 一种用于推理具有语义网络的概念，关系和规则的系统和方法，所述概念，关系和规则包括来自预定的一组节点类型的至少一个节点，来自预定的一组链路类型的至少一个链路以及来自预定集合的零个或多个规则 规则类型的一部分，规则类型的一部分是匹配规则类型，每个节点和每个链接与一组零个或多个规则相关联; 具有至少一个正则表达式的推理类型数据库的网络推理数据结构，每个正则表达式是具有至少三种节点类型和两种链接类型的序列类别，其中所述网络推理数据结构还具有上下文为 一套规则; 以及具有用于激活所述语义网络中的一个或多个激活路径的激活器的推理引擎，所述激活路径集合具有所述语义网络中的公共起始节点，其中所述推理引擎还具有用于选择所述激活路径的子集的验证器 作为有效路径，来自与在上下文中的一个或多个规则匹配的每个有效路径上的一个或多个路径元素相关联的规则匹配类型的集合中的每个规则，并且其中所述推理引擎还具有用于选择子集的合法参考 的有效路径集合是合法且有效的路径，合法和有效路径与至少一个正则表达式匹配。
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7.发明授权Method and knowledge structures for reasoning about concepts, relations, and rules 有权关于概念，关系和规则推理的方法和知识结构公开(公告)号：US07447667B2
公开(公告)日：2008-11-04
申请号：US10316588
申请日：2002-12-11
IPC分类号： G06N5/00
CPC分类号： G06N5/04 , Y10S707/99935
摘要： A system and method for reasoning about concepts, relations and rules having a semantic network comprising at least one node from a predetermined set of node types, at least one link from a predetermined set of link types, and zero or more rules from a predetermined set of rule types, a subset of the rule types being matching rule types, each node and each link being associated with a set of zero or more rules; a network reasoning data structure having a reasoning type database having at least one regular expression, each of the regular expressions being a class of sequences having at least three node types and two link types, wherein the network reasoning data structure further has a context being a set of rules; and a reasoning engine having an activator for activating one or more activated paths in the semantic network, the set of activated paths having a common starting node in the semantic network, wherein the reasoning engine further has a validator for selecting a subset of the activated paths being valid paths, each rule from the set of rule matching types that is associated with one or more path elements on each valid path being matched by one or more rules in the context and wherein the reasoning engine further has a legal inferencer for selecting a subset of the set of valid paths being legal and valid paths, the legal and valid paths matching at least one of the regular expressions.
摘要翻译： 一种用于推理具有语义网络的概念，关系和规则的系统和方法，所述概念，关系和规则包括来自预定的一组节点类型的至少一个节点，来自预定的一组链路类型的至少一个链路以及来自预定集合的零个或多个规则 规则类型的一部分，规则类型的一部分是匹配规则类型，每个节点和每个链接与一组零个或多个规则相关联; 具有至少一个正则表达式的推理类型数据库的网络推理数据结构，每个正则表达式是具有至少三种节点类型和两种链接类型的序列类别，其中所述网络推理数据结构还具有上下文为 一套规则; 以及具有用于激活所述语义网络中的一个或多个激活路径的激活器的推理引擎，所述激活路径集合具有所述语义网络中的公共起始节点，其中所述推理引擎还具有用于选择所述激活路径的子集的验证器 作为有效路径，来自与在上下文中的一个或多个规则匹配的每个有效路径上的一个或多个路径元素相关联的规则匹配类型的集合中的每个规则，并且其中所述推理引擎还具有用于选择子集的合法参考 的有效路径集合是合法且有效的路径，合法和有效路径与至少一个正则表达式匹配。
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8.发明授权System and method for automatic recognition and labeling of anatomical structures and vessels in medical imaging scans 有权用于医学影像扫描中解剖结构和血管的自动识别和标记的系统和方法公开(公告)号：US08761475B2
公开(公告)日：2014-06-24
申请号：US13552160
申请日：2012-07-18
CPC分类号： G06K9/6206 , G06K2209/05 , G06T7/11 , G06T7/149 , G06T7/187 , G06T2207/30012 , G06T2207/30101
摘要： A system and method for recognizing and labeling anatomical structures in an image includes creating a list of objects such that one or more objects on the list appear before a target object and setting the image as a context for a first object on the list. The first object is detected and labeled by subtracting a background of the image. A local context is set for a next object on the list using the first object. The next object is detected and labeled by registration using the local context. Setting a local context and detecting and labeling the next object are repeated until the target object is detected and labeled. Labeling of the target object is refined using region growing.
摘要翻译： 用于识别和标记图像中的解剖结构的系统和方法包括创建对象的列表，使得列表上的一个或多个对象出现在目标对象之前并且将图像设置为列表中的第一对象的上下文。 通过减去图像的背景来检测和标记第一个对象。 使用第一个对象为列表上的下一个对象设置本地上下文。 通过使用本地上下文的注册来检测和标记下一个对象。 重复设置本地上下文并检测和标记下一个对象，直到检测到目标对象并标记为止。 目标对象的标注使用区域增长进行细化。
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9.发明授权Method and knowledge structures for reasoning about concepts, relations, and rules 有权关于概念，关系和规则推理的方法和知识结构公开(公告)号：US07844562B2
公开(公告)日：2010-11-30
申请号：US12261541
申请日：2008-10-30
IPC分类号： G06N5/00
CPC分类号： G06N5/04 , Y10S707/99935
摘要： A system and method for reasoning about concepts, relations and rules having a semantic network comprising at least one node from a predetermined set of node types, at least one link from a predetermined set of link types, and zero or more rules from a predetermined set of rule types, a subset of the rule types being matching rule types, each node and each link being associated with a set of zero or more rules; a network reasoning data structure having a reasoning type database having at least one regular expression, each of the regular expressions being a class of sequences having at least three node types and two link types, wherein the network reasoning data structure further has a context being a set of rules; and a reasoning engine having an activator for activating one or more activated paths in the semantic network, the set of activated paths having a common starting node in the semantic network, wherein the reasoning engine further has a validator for selecting a subset of the activated paths being valid paths, each rule from the set of rule matching types that is associated with one or more path elements on each valid path being matched by one or more rules in the context and wherein the reasoning engine further has a legal inferencer for selecting a subset of the set of valid paths being legal and valid paths, the legal and valid paths matching at least one of the regular expressions.
摘要翻译： 一种用于推理具有语义网络的概念，关系和规则的系统和方法，所述概念，关系和规则包括来自预定的一组节点类型的至少一个节点，来自预定的一组链路类型的至少一个链路以及来自预定集合的零个或多个规则 规则类型的一部分，规则类型的一部分是匹配规则类型，每个节点和每个链接与一组零个或多个规则相关联; 具有至少一个正则表达式的推理类型数据库的网络推理数据结构，每个正则表达式是具有至少三种节点类型和两种链接类型的序列类别，其中所述网络推理数据结构还具有上下文为 一套规则; 以及具有用于激活所述语义网络中的一个或多个激活路径的激活器的推理引擎，所述激活路径集合具有所述语义网络中的公共起始节点，其中所述推理引擎还具有用于选择所述激活路径的子集的验证器 作为有效路径，来自与在上下文中的一个或多个规则匹配的每个有效路径上的一个或多个路径元素相关联的规则匹配类型的集合中的每个规则，并且其中所述推理引擎还具有用于选择子集的合法参考 的有效路径集合是合法且有效的路径，合法和有效路径与至少一个正则表达式匹配。
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