专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 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。

2. 发明授权

US08150116B2 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：US08150116B2
公开(公告)日：2012-04-03
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： G06K17/00
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。目标可变形结构通过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。

3. 发明授权

US08170303B2 Automatic cardiac view classification of echocardiography 有权
标题翻译：自动心脏超声心动图分类
公开(公告)号：US08170303B2
公开(公告)日：2012-05-01
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。

4. 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。

5. 发明授权

US08092388B2 Automated view classification with echocardiographic data for gate localization or other purposes 有权
标题翻译：用于门定位或其他目的的超声心动图数据的自动视图分类
公开(公告)号：US08092388B2
公开(公告)日：2012-01-10
申请号：US12210419
申请日：2008-09-15
申请人： Jin Hyeong Park , Shaohua Kevin Zhou , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu
发明人： Jin Hyeong Park , Shaohua Kevin Zhou , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu
IPC分类号： A61B8/00 , A61B8/08
CPC分类号： G06K9/6257 , G06K9/6292 , G06K2209/05
摘要： A view represented by echocardiographic data is classified. A probabilistic boosting network is used to classify the view. The probabilistic boosting network may include multiple levels where each level has a multi-class local structure classifier and a plurality of local-structure detectors corresponding to the respective multiple classes. In each level, the local structure is classified as a particular view and then the local structure is detected to determine whether the currently selected local structure corresponds to the class. The view classification may be used to determine gate locations, such as a gate for spectral Doppler analysis.
摘要翻译：以超声心动图数据为代表的视图进行分类。概率增强网络用于对视图进行分类。概率增强网络可以包括多个级别，其中每个级别具有多类本地结构分类器和对应于相应的多个类别的多个局部结构检测器。在每个级别中，将本地结构分类为特定视图，然后检测本地结构以确定当前选择的本地结构是否对应于该类。视图分类可用于确定门位置，例如用于频谱多普勒分析的门。

6. 发明申请

US20090088640A1 Automated View Classification With Echocardiographic Data For Gate Localization Or Other Purposes 有权
标题翻译：自动视图分类与超声心动图数据门定位或其他目的
公开(公告)号：US20090088640A1
公开(公告)日：2009-04-02
申请号：US12210419
申请日：2008-09-15
申请人： Jin Hyeong Park , Shaohua Kevin Zhou , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu
发明人： Jin Hyeong Park , Shaohua Kevin Zhou , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu
IPC分类号： A61B8/00 , G06F17/30
CPC分类号： G06K9/6257 , G06K9/6292 , G06K2209/05
摘要： A view represented by echocardiographic data is classified. A probabilistic boosting network is used to classify the view. The probabilistic boosting network may include multiple levels where each level has a multi-class local structure classifier and a plurality of local-structure detectors corresponding to the respective multiple classes. In each level, the local structure is classified as a particular view and then the local structure is detected to determine whether the currently selected local structure corresponds to the class. The view classification may be used to determine gate locations, such as a gate for spectral Doppler analysis.
摘要翻译：以超声心动图数据为代表的视图进行分类。概率增强网络用于对视图进行分类。概率增强网络可以包括多个级别，其中每个级别具有多类本地结构分类器和对应于相应的多个类别的多个局部结构检测器。在每个级别中，将本地结构分类为特定视图，然后检测本地结构以确定当前选择的本地结构是否对应于该类。视图分类可用于确定门位置，例如用于频谱多普勒分析的门。

7. 发明授权

US07648460B2 Medical diagnostic imaging optimization based on anatomy recognition 有权
标题翻译：基于解剖识别的医学诊断成像优化
公开(公告)号：US07648460B2
公开(公告)日：2010-01-19
申请号：US11513675
申请日：2006-08-30
申请人： Constantine Simopoulos , Shaohua Kevin Zhou , Jin-hyeong Park , Dorin Comaniciu , Bogdan Georgescu
发明人： Constantine Simopoulos , Shaohua Kevin Zhou , Jin-hyeong Park , Dorin Comaniciu , Bogdan Georgescu
IPC分类号： A61B17/00
CPC分类号： A61B8/00 , A61B6/503 , A61B8/0883 , G06F19/00 , G06F19/321 , G16H50/20
摘要： Anatomical information is identified from a medical image and/or used for controlling a medical diagnostic imaging system, such as an ultrasound system. To identify anatomical information from a medical image, a processor applies a multi-class classifier. The anatomical information is used to set an imaging parameter of the medical imaging system. The setting or identification may be used in combination or separately.
摘要翻译：解剖信息从医学图像识别和/或用于控制诸如超声系统的医学诊断成像系统。为了从医学图像中识别解剖信息，处理器应用多类分类器。解剖信息用于设置医学成像系统的成像参数。设置或标识可以组合使用或分开使用。

8. 发明授权

US08295569B2 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的自动检测和测量方法及系统
公开(公告)号：US08295569B2
公开(公告)日：2012-10-23
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。

9. 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。

10. 发明申请

US20080009722A1 Multi-planar reconstruction for ultrasound volume data 审中-公开
标题翻译：超声体积数据的多平面重建
公开(公告)号：US20080009722A1
公开(公告)日：2008-01-10
申请号：US11527286
申请日：2006-09-25
申请人： Constantine Simopoulos , Lewis J. Thomas , Shaohua Kevin Zhou , Dorin Comaniciu , Bogdan Georgescu
发明人： Constantine Simopoulos , Lewis J. Thomas , Shaohua Kevin Zhou , Dorin Comaniciu , Bogdan Georgescu
IPC分类号： A61B8/00
CPC分类号： G01S7/52036 , A61B8/08 , A61B8/0883 , A61B8/0891 , A61B8/14 , A61B8/483 , A61B8/488 , A61B8/523 , G01S7/52068 , G01S7/52088 , G01S15/8993
摘要： During scanning or in real-time with acquisition of ultrasound data, a plurality of images is generated corresponding to a plurality of different planes in a volume. The volume scan data is searched by a processor to identify desired views. Multiple standard or predetermined views are generated based on plane positioning within the volume by the processor. Multi-planar reconstruction, guided by the processor, allows for real-time imaging of multiple views at a substantially same time. The images corresponding to the identified views are generated independent of the position of the transducer. The planes may be positioned in real-time using a pyramid data structure of coarse and fine data sets.
摘要翻译：在扫描期间或通过获取超声数据实时地生成与体积中的多个不同平面对应的多个图像。卷处理器搜索卷扫描数据以识别所需视图。基于处理器在卷内的平面定位产生多个标准或预定视图。由处理器引导的多平面重建允许在大致相同的时间对多个视图进行实时成像。与所识别的视图相对应的图像独立于换能器的位置产生。可以使用粗略和精细数据集的金字塔数据结构实时定位平面。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式