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1. 发明申请

US20140086465A1 MULTI-BONE SEGMENTATION FOR 3D COMPUTED TOMOGRAPHY 有权
标题翻译：用于3D计算机图像的多骨段分割
公开(公告)号：US20140086465A1
公开(公告)日：2014-03-27
申请号：US13953825
申请日：2013-07-30
申请人： Dijia Wu , Neil Birkbeck , Michal Sofka , Meizhu Liu , Shaohua Kevin Zhou
发明人： Dijia Wu , Neil Birkbeck , Michal Sofka , Meizhu Liu , Shaohua Kevin Zhou
IPC分类号： G06T7/00
CPC分类号： G06T7/0079 , G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/10072 , G06T2207/20041 , G06T2207/20076
摘要： Multiple object segmentation is performed for three-dimensional computed tomography. The adjacent objects are individually segmented. Overlapping regions or locations designated as belonging to both objects may be identified. Confidence maps for the individual segmentations are used to label the locations of the overlap as belonging to one or the other object, not both. This re-segmentation is applied for the overlapping local, and not other locations. Confidence maps in re-segmentation and application just to overlap locations may be used independently of each other or in combination.
摘要翻译：对三维计算机断层摄影进行多目标分割。相邻的对象被单独分段。可以识别指定为属于两个对象的重叠区域或位置。用于各个分段的置信图用于将重叠的位置标记为属于一个或另一个对象，而不是两者。这种重新分割被应用于重叠的本地，而不是其他位置。重新分割和应用恰好重叠位置的置信度图可以彼此独立地或组合地使用。

2. 发明授权

US09495752B2 Multi-bone segmentation for 3D computed tomography 有权
标题翻译：用于3D计算机断层扫描的多骨分割
公开(公告)号：US09495752B2
公开(公告)日：2016-11-15
申请号：US13953825
申请日：2013-07-30
申请人： Dijia Wu , Neil Birkbeck , Michal Sofka , Meizhu Liu , Shaohua Kevin Zhou
发明人： Dijia Wu , Neil Birkbeck , Michal Sofka , Meizhu Liu , Shaohua Kevin Zhou
IPC分类号： G06T7/00
CPC分类号： G06T7/0079 , G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/10072 , G06T2207/20041 , G06T2207/20076
摘要： Multiple object segmentation is performed for three-dimensional computed tomography. The adjacent objects are individually segmented. Overlapping regions or locations designated as belonging to both objects may be identified. Confidence maps for the individual segmentations are used to label the locations of the overlap as belonging to one or the other object, not both. This re-segmentation is applied for the overlapping local, and not other locations. Confidence maps in re-segmentation and application just to overlap locations may be used independently of each other or in combination.
摘要翻译：对三维计算机断层摄影进行多目标分割。相邻的对象被单独分段。可以识别指定为属于两个对象的重叠区域或位置。用于各个分段的置信图用于将重叠的位置标记为属于一个或另一个对象，而不是两者。这种重新分割被应用于重叠的本地，而不是其他位置。重新分割和应用恰好重叠位置的置信度图可以彼此独立地或组合地使用。

3. 发明授权

US09646229B2 Method and system for bone segmentation and landmark detection for joint replacement surgery 有权
公开(公告)号：US09646229B2
公开(公告)日：2017-05-09
申请号：US14041029
申请日：2013-09-30
申请人： Michal Sofka , Meizhu Liu , Dijia Wu , Shaohua Kevin Zhou
发明人： Michal Sofka , Meizhu Liu , Dijia Wu , Shaohua Kevin Zhou
IPC分类号： G06K9/00 , G06K9/66 , G06T7/00 , G06T7/10
CPC分类号： G06K9/66 , G06T7/0014 , G06T7/10 , G06T2207/10081 , G06T2207/10088 , G06T2207/20081 , G06T2207/30004
摘要： A method and system for automatic bone segmentation and landmark detection for joint replacement surgery is disclosed. A 3D medical image of at least a target joint region of a patient is received. A plurality bone structures are automatically segmented in the target joint region of the 3D medical image and a plurality of landmarks associated with a joint replacement surgery are automatically detected in the target joint region of the 3D medical image. The boundaries of segmented bone structures can then be interactively refined based on user inputs.

4. 发明申请

US20140093153A1 Method and System for Bone Segmentation and Landmark Detection for Joint Replacement Surgery 有权
标题翻译：骨关节置换术和地标检测方法与系统
公开(公告)号：US20140093153A1
公开(公告)日：2014-04-03
申请号：US14041029
申请日：2013-09-30
申请人： Michal Sofka , Meizhu Liu , Dijia Wu , Shaohua Kevin Zhou
发明人： Michal Sofka , Meizhu Liu , Dijia Wu , Shaohua Kevin Zhou
IPC分类号： G06T7/00 , G06K9/66
CPC分类号： G06K9/66 , G06T7/0014 , G06T7/10 , G06T2207/10081 , G06T2207/10088 , G06T2207/20081 , G06T2207/30004
摘要： A method and system for automatic bone segmentation and landmark detection for joint replacement surgery is disclosed. A 3D medical image of at least a target joint region of a patient is received. A plurality bone structures are automatically segmented in the target joint region of the 3D medical image and a plurality of landmarks associated with a joint replacement surgery are automatically detected in the target joint region of the 3D medical image. The boundaries of segmented bone structures can then be interactively refined based on user inputs.
摘要翻译：公开了一种用于关节置换手术的自动骨分割和地标检测的方法和系统。接收患者的至少目标关节区域的3D医学图像。在3D医疗图像的目标关节区域中自动分割多个骨骼结构，并且在3D医疗图像的目标关节区域中自动检测与关节置换手术相关联的多个界标。然后可以基于用户输入交互地改进分段骨结构的边界。

5. 发明授权

US09218524B2 Automatic spatial context based multi-object segmentation in 3D images 有权
标题翻译：在3D图像中基于自动空间上下文的多对象分割
公开(公告)号：US09218524B2
公开(公告)日：2015-12-22
申请号：US13776184
申请日：2013-02-25
申请人： Quan Wang , Dijia Wu , Meizhu Liu , Le Lu , Kevin Shaohua Zhou
发明人： Quan Wang , Dijia Wu , Meizhu Liu , Le Lu , Kevin Shaohua Zhou
IPC分类号： G06K9/00 , G06T7/00 , G06K9/62
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 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 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性形状模型细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生成到骨区域和软骨区域中。

6. 发明申请

US20140161334A1 AUTOMATIC SPATIAL CONTEXT BASED MULTI-OBJECT SEGMENTATION IN 3D IMAGES 有权
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：US20140161334A1
公开(公告)日：2014-06-12
申请号：US13776184
申请日：2013-02-25
申请人： Quan Wang , Dijia Wu , Meizhu Liu , Le Lu , Kevin Shaohua Zhou
发明人： Quan Wang , Dijia Wu , Meizhu Liu , Le Lu , Kevin Shaohua Zhou
IPC分类号： G06K9/00
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 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 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性形状模型细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生成到骨区域和软骨区域中。

7. 发明授权

US08885898B2 Matching of regions of interest across multiple views 有权
标题翻译：在多个视图中匹配感兴趣的区域
公开(公告)号：US08885898B2
公开(公告)日：2014-11-11
申请号：US13267095
申请日：2011-10-06
申请人： Meizhu Liu , Le Lu , Vikas C. Raykar , Marcos Salganicoff , Matthias Wolf
发明人： Meizhu Liu , Le Lu , Vikas C. Raykar , Marcos Salganicoff , Matthias Wolf
IPC分类号： G06K9/00 , G06T7/00 , G06K9/62 , A61B6/03 , A61B8/13
CPC分类号： G06K9/6215 , A61B6/032 , A61B6/037 , A61B8/13 , G06T7/0014 , G06T7/30 , G06T2207/10072 , G06T2207/20081 , G06T2207/30032
摘要： Described herein is a framework for multi-view matching of regions of interest in images. According to one aspect, a processor receives first and second digitized images, as well as at least one CAD finding corresponding to a detected region of interest in the first image. The processor determines at least one candidate location in the second image that matches the CAD finding in the first image. The matching is performed based on local appearance features extracted for the CAD finding and the candidate location. In accordance with another aspect, the processor receives digitized training images representative of at least first and second views of one or more regions of interest. Feature selection is performed based on the training images to select a subset of relevant local appearance features to represent instances in the first and second views. A distance metric is then learned based on the subset of local appearance features. The distance metric may be used to perform matching of the regions of interest.
摘要翻译：这里描述了用于图像中感兴趣区域的多视图匹配的框架。根据一个方面，处理器接收第一和第二数字化图像，以及对应于第一图像中检测到的感兴趣区域的至少一个CAD查找。处理器确定与第一图像中的CAD查找匹配的第二图像中的至少一个候选位置。基于为CAD查找和候选位置提取的本地外观特征执行匹配。根据另一方面，处理器接收代表一个或多个感兴趣区域的至少第一和第二视图的数字化的训练图像。基于训练图像执行特征选择，以选择相关局部外观特征的子集来表示第一和第二视图中的实例。然后基于局部外观特征的子集来学习距离度量。距离度量可以用于执行感兴趣区域的匹配。

8. 发明申请

US20120088981A1 Matching of Regions of Interest Across Multiple Views 有权
标题翻译：多个意见区域的匹配
公开(公告)号：US20120088981A1
公开(公告)日：2012-04-12
申请号：US13267095
申请日：2011-10-06
申请人： Meizhu Liu , Le Lu , Vikas C. Raykar , Marcos Salganicoff , Matthias Wolf
发明人： Meizhu Liu , Le Lu , Vikas C. Raykar , Marcos Salganicoff , Matthias Wolf
IPC分类号： A61B5/00 , G06K9/00
CPC分类号： G06K9/6215 , A61B6/032 , A61B6/037 , A61B8/13 , G06T7/0014 , G06T7/30 , G06T2207/10072 , G06T2207/20081 , G06T2207/30032
摘要： Described herein is a framework for multi-view matching of regions of interest in images. According to one aspect, a processor receives first and second digitized images, as well as at least one CAD finding corresponding to a detected region of interest in the first image. The processor determines at least one candidate location in the second image that matches the CAD finding in the first image. The matching is performed based on local appearance features extracted for the CAD finding and the candidate location. In accordance with another aspect, the processor receives digitized training images representative of at least first and second views of one or more regions of interest. Feature selection is performed based on the training images to select a subset of relevant local appearance features to represent instances in the first and second views. A distance metric is then learned based on the subset of local appearance features. The distance metric may be used to perform matching of the regions of interest.
摘要翻译：这里描述了用于图像中感兴趣区域的多视图匹配的框架。根据一个方面，处理器接收第一和第二数字化图像，以及对应于第一图像中检测到的感兴趣区域的至少一个CAD查找。处理器确定与第一图像中的CAD查找匹配的第二图像中的至少一个候选位置。基于为CAD查找和候选位置提取的本地外观特征执行匹配。根据另一方面，处理器接收代表一个或多个感兴趣区域的至少第一和第二视图的数字化的训练图像。基于训练图像执行特征选择，以选择相关局部外观特征的子集来表示第一和第二视图中的实例。然后基于局部外观特征的子集来学习距离度量。距离度量可以用于执行感兴趣区域的匹配。

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