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61. 发明申请

US20090310837A1 Method and System for Automatic Detection and Measurement of Mitral Valve Inflow Patterns in Doppler Echocardiography 有权
标题翻译：多普勒超声心动图二尖瓣流入模式自动检测和测量方法与系统
公开(公告)号：US20090310837A1
公开(公告)日：2009-12-17
申请号：US12481861
申请日：2009-06-10
申请人： Jin-hyeong Park , Shaohua Kevin Zhou , John I. Jackson , Dorin Comaniciu
发明人： Jin-hyeong Park , Shaohua Kevin Zhou , John I. Jackson , Dorin Comaniciu
IPC分类号： G06K9/00
CPC分类号： G06K9/0053 , A61B8/0883 , A61B8/488 , G06K2209/05
摘要： A method and system for segmentation of mitral valve inflow (MI) patterns in Doppler echocardiogram images is disclosed. Trained root detectors are used to detect left root candidates, right root candidates, and peak candidates in an input Doppler echocardiogram image. Two global structure detectors, a single triangle detector for non-overlapping E-waves and A-waves and a double triangle detector for overlapping E-waves and A-waves, are used to detect single triangle candidates and double triangle candidates based on the left root, right root, and peak candidates. A shape profile is used to determine a shape probability for each of the single triangle candidates and each of the double triangle candidates. The best single triangle candidate and the best double triangle candidate are selected based on shape probability and detection probability. One of the best single triangle candidate and the best double triangle candidate is selected as the final segmentation result based on a shape probability comparison.
摘要翻译：公开了一种用于多普勒超声心动图图像中二尖瓣流入（MI）模式分割的方法和系统。训练的根检测器用于检测输入多普勒超声心动图图像中的左根候选，右根候选和峰候选。两个全局结构检测器，用于非重叠E波和A波的单个三角形检测器和用于重叠E波和A波的双三角形检测器用于基于左侧检测单个三角形候选和双三角形候选根，右根和峰值候选。形状轮廓用于确定每个单个三角形候选和每个双三角形候选的形状概率。基于形状概率和检测概率选择最佳单三角候选和最佳双三角候选。基于形状概率比较，选择最佳单三角候选和最佳双三角候选之一作为最终分割结果。

62. 发明申请

US20090034808A1 Automatic Cardiac View Classification of Echocardiography 有权
标题翻译：超声心动图自动心脏视图分类
公开(公告)号：US20090034808A1
公开(公告)日：2009-02-05
申请号：US11775538
申请日：2007-07-10
申请人： Shaohua Kevin Zhou , Jin-Hyeong Park , Joanne Otsuki , Dorin Comaniciu , Bogdan Georgescu , Constantine Simopoulos
发明人： Shaohua Kevin Zhou , Jin-Hyeong Park , Joanne Otsuki , Dorin Comaniciu , Bogdan Georgescu , Constantine Simopoulos
IPC分类号： G06K9/00
CPC分类号： G06K9/6256 , G06K9/6292 , G06K2209/051
摘要： A method for view classification includes providing a frame of an object of interest, detecting a region of interest within the object of interest for each of a plurality of detectors (e.g., binary classifiers), wherein each binary classifier corresponds to a different view, performing a global view classification using a multiview classifier for each view, outputting a classification for each view, fusing outputs of the multiview classifiers, and determining and outputting a classification of the frame based on a fused output of the multiview classifiers.
摘要翻译：一种用于视图分类的方法包括提供感兴趣对象的帧，检测多个检测器（例如，二进制分类器）中的每一个的感兴趣对象内的感兴趣区域，其中每个二进制分类器对应于不同视图，执行对于每个视图使用多视角分类器的全局视图分类，输出每个视图的分类，融合多视角分类器的输出，以及基于多视角分类器的融合输出来确定和输出该帧的分类。

63. 发明申请

US20090010509A1 Method and system for detection of deformable structures in medical images 有权
标题翻译：用于检测医学图像中可变形结构的方法和系统
公开(公告)号：US20090010509A1
公开(公告)日：2009-01-08
申请号：US12214339
申请日：2008-06-18
申请人： Shaohua Kevin Zhou , Feng Guo , Jin-Hyeong Park , Gustavo Henrique Monteiro de Barros Carneiro , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu , John I. Jackson
发明人： Shaohua Kevin Zhou , Feng Guo , Jin-Hyeong Park , Gustavo Henrique Monteiro de Barros Carneiro , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu , John I. Jackson
IPC分类号： G06K9/62
CPC分类号： G06K9/0055 , G06K9/6206 , G06K9/6256
摘要： A method and system for detection of deformable structures in medical images is disclosed. Deformable structures can represent blood flow patterns in images such as Doppler echocardiograms. A probabilistic, hierarchical, and discriminant framework is used to detect such deformable structures. This framework integrates evidence from different primitive levels via a progressive detector hierarchy, including a series of discriminant classifiers. A target deformable structure is parameterized by a multi-dimensional parameter, and primitives or partial parameterizations of the parameter are determined. An input image is received, and a series of primitives are sequentially detected using the progressive detector hierarchy, in which each detector or classifier detects a corresponding primitive. The final detector detects configuration candidates for the deformable structure.
摘要翻译：公开了用于检测医学图像中的可变形结构的方法和系统。可变形结构可以表示图像中的血流模式，例如多普勒超声心动图。概率，分层和判别框架用于检测这种可变形结构。该框架通过渐进式检测器层次结合不同原始级别的证据，包括一系列判别分类器。目标可变形结构由多维参数进行参数化，并确定参数的基元或部分参数化。接收输入图像，并且使用逐行检测器层级顺序地检测一系列图元，其中每个检测器或分类器检测相应的图元。最终检测器检测可变形结构的配置候选。

64. 发明申请

US20080281203A1 System and Method for Quasi-Real-Time Ventricular Measurements From M-Mode EchoCardiogram 有权
标题翻译：从M模式回波心电图准确实时心室测量的系统和方法
公开(公告)号：US20080281203A1
公开(公告)日：2008-11-13
申请号：US12054094
申请日：2008-03-24
申请人： Shaohua Kevin Zhou , Feng Guo , John Jackson , Michael Brendel , Dorin Comaniciu
发明人： Shaohua Kevin Zhou , Feng Guo , John Jackson , Michael Brendel , Dorin Comaniciu
IPC分类号： A61B8/00
CPC分类号： A61B8/08 , A61B5/1075 , A61B5/7267 , A61B6/503 , A61B8/0883 , A61B8/463 , A61B8/486 , G06K9/00523 , G06K9/00536 , G06K9/6257 , G06T7/60
摘要： A method for measuring ventricular dimensions from M-mode echocardiograms, includes providing a digitized M-mode echocardiogram image, running a plurality of local classifiers, where each local classifier trained to detect a landmark on either an end-diastole (ED) line or an end-systole (ES) line in the image, recording all possible landmarks detected by the classifiers, where a search range in an N-dimensional parameter space defined by the landmarks for each dimension is reduced to a union of subsets, where each dimension of the parameter space corresponds a landmark, for each combination of possible landmarks, checking if an order of the landmarks is consistent with a known ordering of the landmarks, and if the order is consistent, running a global detector on each consistent combination of landmarks to find a landmark combination with a highest detection probability as a confirmed landmark detection, where the landmarks are used for measuring ventricular dimensions.
摘要翻译：一种用于从M型超声心动图测量心室尺寸的方法，包括提供数字化的M模式超声心动图图像，运行多个局部分类器，其中训练每个局部分类器以检测舒张末期（ED）线或记录图像中的终点收缩（ES）线，记录由分类器检测到的所有可能的地标，其中由每个维度的地标定义的N维参数空间中的搜索范围被减少到子集的并集，其中每个维度参数空间对应于地标，对于可能的地标的每个组合，检查地标的顺序是否与已知的地标的顺序一致，并且如果顺序一致，则在每个一致的地标组合上运行全局检测器以找到具有最高检测概率的地标组合，作为确认的地标检测，其中地标被用于测量心室维度。

65. 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。

66. 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。

67. 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.

68. 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。

69. 发明申请

US20120070074A1 Method and System for Training a Landmark Detector using Multiple Instance Learning 有权
标题翻译：使用多实例学习训练地标检测器的方法和系统
公开(公告)号：US20120070074A1
公开(公告)日：2012-03-22
申请号：US13228509
申请日：2011-09-09
申请人： David Liu , Shaohua Kevin Zhou
发明人： David Liu , Shaohua Kevin Zhou
IPC分类号： G06K9/62
CPC分类号： G06K9/6257 , G06K2209/051
摘要： An apparatus and method for training a landmark detector receives training data which includes a plurality of positive training bags, each including a plurality of positively annotated instances, and a plurality of negative training bags, each including at least one negatively annotated instance. Classification function is initialized by training a first weak classifier based on the positive training bags and the negative training bags. All training instances are evaluated using the classification function. For each of a plurality of remaining classifiers, a cost value gradient is calculated based on spatial context information of each instance in each positive bag evaluated by the classification function. A gradient value associated with each of the remaining weak classifiers is calculated based on the cost value gradients, and a weak classifier is selected which has a lowest associated gradient value and given a weighting parameter and added to the classification function.
摘要翻译：用于训练地标检测器的装置和方法接收训练数据，训练数据包括多个正训练袋，每个正训练袋包括多个带有正面注释的实例，以及多个负训练袋，每个包括至少一个负注释实例。基于积极的训练袋和负面训练袋训练第一个弱分类器来初始化分类功能。使用分类函数评估所有训练实例。对于多个剩余分类器中的每一个，基于由分类函数评估的每个正包中的每个实例的空间上下文信息来计算成本值梯度。基于成本值梯度计算与剩余弱分类器中的每一个相关联的梯度值，并且选择具有最低相关梯度值并给出加权参数并加到分类函数的弱分类器。

70. 发明申请

US20130177230A1 IMPLANT POSE DETERMINATION IN MEDICAL IMAGING 有权
标题翻译：在医学成像中的植入位置确定
公开(公告)号：US20130177230A1
公开(公告)日：2013-07-11
申请号：US13735112
申请日：2013-01-07
申请人： Shaolei Feng , Shaohua Kevin Zhou , Gerhard Kleinszig , Rainer Graumann
发明人： Shaolei Feng , Shaohua Kevin Zhou , Gerhard Kleinszig , Rainer Graumann
IPC分类号： G06T7/00
CPC分类号： G06T7/0012 , G06T7/75 , G06T2207/10116 , G06T2207/30052
摘要： The pose of an implant represented in a medical image is determined from the medical image. The x-ray image of the implant is compared to a database of the implant viewed at different poses (e.g., viewed from different directions). The implant pose associated with the best match indicates the pose of the implant in the x-ray image.
摘要翻译：根据医学图像确定在医学图像中表示的植入物的姿势。将植入物的x射线图像与在不同姿势（例如从不同方向观察）观察的植入物的数据库进行比较。与最佳匹配关联的植入姿势表示植入物在X射线图像中的姿态。

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