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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。
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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。
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3.发明授权公开(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
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.
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4.发明申请公开(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
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。
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5.发明授权Method and system for automatic rib centerline extraction using learning based deformable template matching 有权使用基于学习的可变形模板匹配的自动肋骨中心线提取的方法和系统公开(公告)号：US08989471B2
公开(公告)日：2015-03-24
申请号：US13602730
申请日：2012-09-04
申请人： Dijia Wu , David Liu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
发明人： Dijia Wu , David Liu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
CPC分类号： G06K9/6207 , G06T7/12 , G06T7/149 , G06T2207/10072 , G06T2207/20081 , G06T2207/20116 , G06T2207/30008 , G06T2207/30172
摘要： A method and system for extracting rib centerlines in a 3D volume, such as a 3D computed tomography (CT) volume, is disclosed. Rib centerline voxels are detected in the 3D volume using a learning based detector. Rib centerlines or the whole rib cage are then extracted by matching a template of rib centerlines for the whole rib cage to the 3D volume based on the detected rib centerline voxels. Each of the extracted rib centerlines are then individually refined using an active contour model.
摘要翻译： 公开了一种用于在3D体积中提取肋骨中心线的方法和系统，例如3D计算机断层摄影（CT）体积。 使用基于学习的检测器在3D体积中检测肋中心线体素。 然后通过将基于检测到的肋骨中心线体素的整个肋骨架的肋骨中心线的模板与3D体积匹配来提取肋中心线或整个肋骨笼。 然后使用主动轮廓模型分别提取每个提取的肋中心线。
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公开(公告)号：US20120106810A1
公开(公告)日：2012-05-03
申请号：US13274515
申请日：2011-10-17
IPC分类号： G06K9/00
CPC分类号： G06T7/73 , G06T2207/10081 , G06T2207/30012 , G06T2207/30064 , G06T2207/30172
摘要： Ribs are automatically ordered and paired. After ordering ribs on each side, magnetic and spring functions are used to solve for rib pairing. The magnetic function is used to constrain possible pairs across sides, and the spring function is used to maintain the order on each side while accounting for missing or fused ribs.
摘要翻译： 肋骨自动排序并配对。 在每侧排列肋后，使用磁力和弹簧功能来解决肋配对。 磁功能用于限制双方的可能对，弹簧功能用于维护每侧的顺序，同时考虑到缺失或融合的肋骨。
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公开(公告)号：US09117259B2
公开(公告)日：2015-08-25
申请号：US13238370
申请日：2011-09-21
申请人： David Liu , Dijia Wu , Shaohua Kevin Zhou , Maria Jimena Costa , Michael Suehling , Christian Tietjen
发明人： David Liu , Dijia Wu , Shaohua Kevin Zhou , Maria Jimena Costa , Michael Suehling , Christian Tietjen
CPC分类号： G06T7/0016 , G06T7/41 , G06T2207/10072 , G06T2207/20012 , G06T2207/20041 , G06T2207/20081 , G06T2207/20104 , G06T2207/30056
摘要： A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification.
摘要翻译： 公开了一种用于自动检测医学图像数据中肝脏病变的方法和系统，如3D CT图像。 肝脏区域被分割成3D图像。 肝脏病变中心候选人在分段肝脏区域检测到。 病变候选者对应于肝脏病变中心候选物，并且使用基于学习的验证从分割的病变候选物检测病变。
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公开(公告)号：US20120070055A1
公开(公告)日：2012-03-22
申请号：US13238370
申请日：2011-09-21
申请人： David Liu , Dijia Wu , Shaohua Kevin Zhou , Maria Jimena Costa , Michael Suehling , Christian Tietjen
发明人： David Liu , Dijia Wu , Shaohua Kevin Zhou , Maria Jimena Costa , Michael Suehling , Christian Tietjen
IPC分类号： G06K9/00
CPC分类号： G06T7/0016 , G06T7/41 , G06T2207/10072 , G06T2207/20012 , G06T2207/20041 , G06T2207/20081 , G06T2207/20104 , G06T2207/30056
摘要： A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification.
摘要翻译： 公开了一种用于自动检测医学图像数据中肝脏病变的方法和系统，如3D CT图像。 肝脏区域被分割成3D图像。 肝脏病变中心候选人在分段肝脏区域检测到。 病变候选者对应于肝脏病变中心候选物，并且使用基于学习的验证从分割的病变候选物检测病变。
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9.发明授权Method and system for automatic detection of spinal bone lesions in 3D medical image data 有权3D医学图像数据中脊髓损伤自动检测方法及系统公开(公告)号：US08693750B2
公开(公告)日：2014-04-08
申请号：US13342248
申请日：2012-01-03
申请人： Michael Wels , Michael Suehling , Shaohua Kevin Zhou , David Liu , Dijia Wu , Christopher V. Alvino , Michael Kelm , Grzegorz Soza , Dorin Comaniciu
发明人： Michael Wels , Michael Suehling , Shaohua Kevin Zhou , David Liu , Dijia Wu , Christopher V. Alvino , Michael Kelm , Grzegorz Soza , Dorin Comaniciu
CPC分类号： G06K9/4614 , G06K9/6256 , G06K2209/055 , G06K2209/40 , G06T7/0012 , G06T2207/10072 , G06T2207/20016 , G06T2207/20081 , G06T2207/30012 , G06T2207/30096
摘要： A method and system for automatic detection and volumetric quantification of bone lesions in 3D medical images, such as 3D computed tomography (CT) volumes, is disclosed. Regions of interest corresponding to bone regions are detected in a 3D medical image. Bone lesions are detected in the regions of interest using a cascade of trained detectors. The cascade of trained detectors automatically detects lesion centers and then estimates lesion size in all three spatial axes. A hierarchical multi-scale approach is used to detect bone lesions using a cascade of detectors on multiple levels of a resolution pyramid of the 3D medical image.
摘要翻译： 公开了一种用于3D医学图像中的骨损伤的自动检测和体积定量的方法和系统，例如3D计算机断层摄影（CT）体积。 在3D医学图像中检测与骨骼区域相对应的兴趣区域。 使用级联的经过训练的检测器在感兴趣的区域中检测到骨损伤。 训练有素的检测器的级联自动检测损伤中心，然后估计所有三个空间轴的病变大小。 使用分级多尺度方法来使用3D医学图像的分辨率金字塔的多个级别上的级联检测器来检测骨损伤。
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10.发明申请Method and System for Automatic Rib Centerline Extraction Using Learning Base Deformable Template Matching 有权使用学习基础变形模板匹配的自动肋中心线提取的方法和系统公开(公告)号：US20130077841A1
公开(公告)日：2013-03-28
申请号：US13602730
申请日：2012-09-04
申请人： Dijia Wu , David Liu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
发明人： Dijia Wu , David Liu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
IPC分类号： G06K9/46
CPC分类号： G06K9/6207 , G06T7/12 , G06T7/149 , G06T2207/10072 , G06T2207/20081 , G06T2207/20116 , G06T2207/30008 , G06T2207/30172
摘要： A method and system for extracting rib centerlines in a 3D volume, such as a 3D computed tomography (CT) volume, is disclosed. Rib centerline voxels are detected in the 3D volume using a learning based detector. Rib centerlines or the whole rib cage are then extracted by matching a template of rib centerlines for the whole rib cage to the 3D volume based on the detected rib centerline voxels. Each of the extracted rib centerlines are then individually refined using an active contour model.
摘要翻译： 公开了一种用于在3D体积中提取肋骨中心线的方法和系统，例如3D计算机断层摄影（CT）体积。 使用基于学习的检测器在3D体积中检测肋中心线体素。 然后通过将基于检测到的肋骨中心线体素的整个肋骨架的肋骨中心线的模板与3D体积匹配来提取肋中心线或整个肋骨笼。 然后使用主动轮廓模型分别提取每个提取的肋中心线。
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