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1. 发明申请

WO2014089455A2 AUTOMATIC SPATIAL CONTEXT BASED MULTI-OBJECT SEGMENTATION IN 3D IMAGES 审中-公开
标题翻译：基于自动空间语境的3D图像多目标分割
公开(公告)号：WO2014089455A2
公开(公告)日：2014-06-12
申请号：PCT/US2013/073614
申请日：2013-12-06
申请人： SIEMENS PRODUCT LIFECYCLE MANAGEMENT SOFTWARE INC. , WANG, Quan , WU, Dijia , LIU, Meizhu , LU, Le , ZHOU, Kevin, Shaohua
发明人： WANG, Quan , WU, Dijia , LIU, Meizhu , LU, Le , ZHOU, Kevin, Shaohua
IPC分类号： G06T7/00
CPC分类号： G06K9/00362 , G06K9/6219 , G06K9/6282 , G06K2209/055 , G06T7/12 , G06T7/149 , G06T2207/10088 , G06T2207/30008
摘要： Methods and systems for automatic classification of images of internal structures of human and animal bodies. A method includes receiving (405) a magnetic resonance (MR) image testing model and determining a testing volume of the testing model that includes areas of the testing model to be classified as bone or cartilage. The method includes modifying the testing model so that the testing volume corresponds to a mean shape and a shape variation space of an active shape model and producing an initial classification of the testing volume by fitting the testing volume to the mean shape and the shape variation space. The method includes producing (425) a refined classification of the testing volume into bone areas and cartilage areas by refining the boundaries of the testing volume with respect to the active shape model and segmenting the MR image testing model into different areas corresponding to bone areas and cartilage areas
摘要翻译：自动分类人体和动物体内部结构图像的方法和系统。一种方法包括接收（405）磁共振（MR）图像测试模型并确定包括要分类为骨或软骨的测试模型的区域的测试模型的测试体积。该方法包括修改测试模型，使得测试体积对应于活动形状模型的平均形状和形状变化空间，并通过将测试体积与平均形状和形状变化空间拟合来产生测试体积的初始分类。该方法包括通过相对于活动形状模型改进测试体积的边界并将MR图像测试模型分割成对应于骨骼区域的不同区域，来将测试体积的精细分类生成（425）到骨区域和软骨区域中，以及软骨区域

2. 发明授权

EP2929509B1 AUTOMATIC SPATIAL CONTEXT BASED MULTI-OBJECT SEGMENTATION IN 3D IMAGES 有权转让
标题翻译：基于自动空间背景的三维图像多目标分割
公开(公告)号：EP2929509B1
公开(公告)日：2017-06-14
申请号：EP13811103.4
申请日：2013-12-06
申请人： Siemens Product Lifecycle Management Software Inc.
发明人： WANG, Quan , WU, Dijia , LIU, Meizhu , LU, Le , ZHOU, Kevin Shaohua
IPC分类号： G06K9/62 , G06T7/00
CPC分类号： G06K9/00362 , G06K9/6219 , G06K9/6282 , G06K2209/055 , G06T7/12 , G06T7/149 , G06T2207/10088 , G06T2207/30008

3. 发明公开

EP2929509A2 AUTOMATIC SPATIAL CONTEXT BASED MULTI-OBJECT SEGMENTATION IN 3D IMAGES 有权转让
标题翻译： 3D-BILDERN中的自动化学机器人KONTEXTBASIERTE SEGMENTIERUNG MEHRERER OBJEKTE
公开(公告)号：EP2929509A2
公开(公告)日：2015-10-14
申请号：EP13811103.4
申请日：2013-12-06
申请人： Siemens Product Lifecycle Management Software Inc.
发明人： WANG, Quan , WU, Dijia , LIU, Meizhu , LU, Le , ZHOU, Kevin, Shaohua
IPC分类号： G06T7/00
CPC分类号： G06K9/00362 , G06K9/6219 , G06K9/6282 , G06K2209/055 , G06T7/12 , G06T7/149 , G06T2207/10088 , G06T2207/30008
摘要： Methods and systems for automatic classification of images of internal structures of human and animal bodies. A method includes receiving (405) a magnetic resonance (MR) image testing model and determining a testing volume of the testing model that includes areas of the testing model to be classified as bone or cartilage. The method includes modifying the testing model so that the testing volume corresponds to a mean shape and a shape variation space of an active shape model and producing an initial classification of the testing volume by fitting the testing volume to the mean shape and the shape variation space. The method includes producing (425) a refined classification of the testing volume into bone areas and cartilage areas by refining the boundaries of the testing volume with respect to the active shape model and segmenting the MR image testing model into different areas corresponding to bone areas and cartilage areas
摘要翻译：自动分类人体和动物体内部结构图像的方法和系统。一种方法包括接收磁共振（MR）图像测试模型并确定包括要分类为骨或软骨的测试模型的区域的测试模型的测试体积。该方法包括修改测试模型，使得测试体积对应于活动形状模型的平均形状和形状变化空间，并通过将测试体积与平均形状和形状变化空间拟合来产生测试体积的初始分类。该方法包括通过相对于活动形状模型精化测试体积的边界并将MR图像测试模型分割成对应于骨区域和软骨区域的不同区域，来将测试体积的精细分类产生到骨区域和软骨区域中。

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