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1.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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2.发明申请Method and System for Automatic Detection of Spinal Bone Lesions in 3D Medical Image Data 有权自动检测3D医学图像数据中脊髓损伤的方法和系统公开(公告)号：US20120183193A1
公开(公告)日：2012-07-19
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
IPC分类号： G06K9/00
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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3.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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4.发明授权Method and system for up-vector detection for ribs in computed tomography volumes 有权计算机断层扫描体积中肋骨向上检测的方法和系统公开(公告)号：US09020233B2
公开(公告)日：2015-04-28
申请号：US13602660
申请日：2012-09-04
申请人： David Liu , Hao Xu , Dijia Wu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
发明人： David Liu , Hao Xu , Dijia Wu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
摘要： A method and system for up-vector detection for ribs in a 3D medical image volume, such as a computed tomography (CT) volume is disclosed. A rib centerline of at least one rib is extracted in a 3D medical image volume. An up-vector is automatically detected at each of a plurality of centerline points of the rib centerline of the at least one rib. The up-vector at each centerline point can be detected using a trained regression function. Alternatively, the up-vector at each centerline point can be detected by detecting an ellipse shape in a cross-sectional rib image generated at each centerline point.
摘要翻译： 公开了一种用于3D医学图像体积中的肋的上矢量检测的方法和系统，例如计算机断层摄影（CT）体积。 在3D医学图像体积中提取至少一个肋的肋中心线。 在至少一个肋的肋中心线的多个中心线点的每一个处自动检测向上矢量。 可以使用经过训练的回归函数检测每个中心线点处的向上矢量。 或者，可以通过在每个中心线点处产生的横截面肋图像中检测椭圆形状来检测每个中心线点处的向上矢量。
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5.发明申请Method and System for Up-Vector Detection for Ribs in Computed Tomography Volumes 有权计算机断层扫描中肋骨上向量检测的方法和系统公开(公告)号：US20130070996A1
公开(公告)日：2013-03-21
申请号：US13602660
申请日：2012-09-04
申请人： David Liu , Hao Xu , Dijia Wu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
发明人： David Liu , Hao Xu , Dijia Wu , Christian Tietjen , Grzegorz Soza , Shaohua Kevin Zhou , Dorin Comaniciu
摘要： A method and system for up-vector detection for ribs in a 3D medical image volume, such as a computed tomography (CT) volume is disclosed. A rib centerline of at least one rib is extracted in a 3D medical image volume. An up-vector is automatically detected at each of a plurality of centerline points of the rib centerline of the at least one rib. The up-vector at each centerline point can be detected using a trained regression function. Alternatively, the up-vector at each centerline point can be detected by detecting an ellipse shape in a cross-sectional rib image generated at each centerline point.
摘要翻译： 公开了一种用于3D医学图像体积中的肋的上矢量检测的方法和系统，例如计算机断层摄影（CT）体积。 在3D医学图像体积中提取至少一个肋的肋中心线。 在至少一个肋的肋中心线的多个中心线点的每一个处自动检测向上矢量。 可以使用经过训练的回归函数检测每个中心线点处的向上矢量。 或者，可以通过在每个中心线点处产生的横截面肋图像中检测椭圆形状来检测每个中心线点处的向上矢量。
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6.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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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：US08571285B2
公开(公告)日：2013-10-29
申请号：US13274515
申请日：2011-10-17
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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9.发明授权Method and system for on-site learning of landmark detection models for end user-specific diagnostic medical image reading 有权用于最终用户特定诊断医学图像阅读的地标检测模型的现场学习方法和系统公开(公告)号：US09113781B2
公开(公告)日：2015-08-25
申请号：US13761263
申请日：2013-02-07
CPC分类号： A61B5/0033 , A61B6/00 , A61B6/025 , A61B6/502 , G06F19/00 , G06F19/321 , G06K9/00 , G06K9/6255 , G06K2209/05
摘要： A method and system for on-line learning of landmark detection models for end-user specific diagnostic image reading is disclosed. A selection of a landmark to be detected in a 3D medical image is received. A current landmark detection result for the selected landmark in the 3D medical image is determined by automatically detecting the selected landmark in the 3D medical image using a stored landmark detection model corresponding to the selected landmark or by receiving a manual annotation of the selected landmark in the 3D medical image. The stored landmark detection model corresponding to the selected landmark is then updated based on the current landmark detection result for the selected landmark in the 3D medical image. The landmark selected in the 3D medical image can be a set of landmarks defining a custom view of the 3D medical image.
摘要翻译： 公开了一种用于在线学习用于最终用户特定诊断图像读取的地标检测模型的方法和系统。 接收在3D医疗图像中检测的地标的选择。 通过使用与所选择的地标相对应的存储的地标检测模型自动检测3D医学图像中的所选地标来确定3D医学图像中所选择的地标的当前地标检测结果，或者通过接收所选地标的手动注释 3D医学图像。 然后基于3D医学图像中所选地标的当前地标检测结果来更新对应于所选地标的所存储的地标检测模型。 在3D医学图像中选择的地标可以是定义3D医学图像的定制视图的一组地标。
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10.发明申请Method and System for On-Site Learning of Landmark Detection Models for End User-Specific Diagnostic Medical Image Reading 有权用于特定于用户的诊断医学图像阅读的地标检测模型的现场学习方法和系统公开(公告)号：US20140219548A1
公开(公告)日：2014-08-07
申请号：US13761263
申请日：2013-02-07
IPC分类号： A61B5/00
CPC分类号： A61B5/0033 , A61B6/00 , A61B6/025 , A61B6/502 , G06F19/00 , G06F19/321 , G06K9/00 , G06K9/6255 , G06K2209/05
摘要： A method and system for on-line learning of landmark detection models for end-user specific diagnostic image reading is disclosed. A selection of a landmark to be detected in a 3D medical image is received. A current landmark detection result for the selected landmark in the 3D medical image is determined by automatically detecting the selected landmark in the 3D medical image using a stored landmark detection model corresponding to the selected landmark or by receiving a manual annotation of the selected landmark in the 3D medical image. The stored landmark detection model corresponding to the selected landmark is then updated based on the current landmark detection result for the selected landmark in the 3D medical image. The landmark selected in the 3D medical image can be a set of landmarks defining a custom view of the 3D medical image.
摘要翻译： 公开了一种用于在线学习用于最终用户特定诊断图像读取的地标检测模型的方法和系统。 接收在3D医疗图像中检测的地标的选择。 通过使用与所选择的地标相对应的存储的地标检测模型自动检测3D医学图像中的所选地标来确定3D医学图像中所选择的地标的当前地标检测结果，或者通过接收所选地标的手动注释 3D医学图像。 然后基于3D医学图像中所选地标的当前地标检测结果来更新对应于所选地标的所存储的地标检测模型。 在3D医学图像中选择的地标可以是定义3D医学图像的定制视图的一组地标。
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