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1. 发明授权

US09414798B2 System and method for automatic trigger-ROI detection and monitoring during bolus tracking 有权
标题翻译：用于自动触发的系统和方法 - 快速追踪期间的ROI检测和监测
公开(公告)号：US09414798B2
公开(公告)日：2016-08-16
申请号：US12729274
申请日：2010-03-23
申请人： Ute Feuerlein , Arun Krishnan , Xiang Sean Zhou
发明人： Ute Feuerlein , Arun Krishnan , Xiang Sean Zhou
IPC分类号： A61B6/00 , A61B6/03 , A61B5/00
CPC分类号： A61B6/504 , A61B5/7285 , A61B6/032 , A61B6/469 , A61B6/481 , A61B6/488 , A61B6/541
摘要： A method for bolus tracking includes acquiring one or more baseline images. One or more trigger regions are automatically established within the baseline images. A bolus is administered. The automatically established trigger regions are monitored for bolus arrival at the one or more trigger regions. Bolus arrival at a volume of interest is forecasted based on the bolus arrival at the one or more trigger regions. A diagnostic scan of the volume of interest is acquired at the forecasted time.
摘要翻译：用于推注跟踪的方法包括获取一个或多个基线图像。在基线图像内自动建立一个或多个触发区域。施用推注。监视自动建立的触发区域，以便推动到达一个或多个触发区域。基于在一个或多个触发区域的推迟到达来预测到达感兴趣的体积。在预测时间内获取感兴趣体积的诊断扫描。

2. 发明申请

US20100249582A1 SYSTEM AND METHOD FOR AUTOMATIC TRIGGER-ROI DETECTION AND MONITORING DURING BOLUS TRACKING 有权
标题翻译：用于自动跟踪ROI检测和监控的系统和方法
公开(公告)号：US20100249582A1
公开(公告)日：2010-09-30
申请号：US12729274
申请日：2010-03-23
申请人： Ute Feuerlein , Arun Krishnan , Xiang Sean Zhou
发明人： Ute Feuerlein , Arun Krishnan , Xiang Sean Zhou
IPC分类号： A61B6/00
CPC分类号： A61B6/504 , A61B5/7285 , A61B6/032 , A61B6/469 , A61B6/481 , A61B6/488 , A61B6/541
摘要： A method for bolus tracking includes acquiring one or more baseline images. One or more trigger regions are automatically established within the baseline images. A bolus is administered. The automatically established trigger regions are monitored for bolus arrival at the one or more trigger regions. Bolus arrival at a volume of interest is forecasted based on the bolus arrival at the one or more trigger regions. A diagnostic scan of the volume of interest is acquired at the forecasted time.
摘要翻译：用于推注跟踪的方法包括获取一个或多个基线图像。在基线图像内自动建立一个或多个触发区域。施用推注。监视自动建立的触发区域，以便推动到达一个或多个触发区域。基于在一个或多个触发区域的推迟到达来预测到达感兴趣的体积。在预测时间内获取感兴趣体积的诊断扫描。

3. 发明申请

US20110142320A1 Systems and Methods for Computer Aided Diagnosis and Decision Support in Whole-Body Imaging 有权
标题翻译：全身成像中计算机辅助诊断和决策支持系统与方法
公开(公告)号：US20110142320A1
公开(公告)日：2011-06-16
申请号：US12968492
申请日：2010-12-15
申请人： Alok Gupta , Arun Krishnan , Xiang Sean Zhou
发明人： Alok Gupta , Arun Krishnan , Xiang Sean Zhou
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06F19/00 , G06F19/321 , G06T7/41 , G06T2207/10081 , G06T2207/10104 , G06T2207/20101 , G06T2207/30004 , G16H50/20
摘要： A system for providing automatic diagnosis and decision support includes: a medical image database; generative learning and modeling modules that build distributional appearance models and spatial relational models of organs or structures using images from the medical image database; a statistical whole-body atlas that includes one or more distributional appearance models and spatial relational models of organs or structure, in one or more whole-body imaging modalities, built by the generative learning and modeling modules; and discriminative learning and modeling modules that build two-class or multi-class classifiers for performing at least one of organ, structure or disease detection or segmentation.
摘要翻译：一种用于提供自动诊断和决策支持的系统包括：医学图像数据库; 生成学习和建模模块，使用医学图像数据库中的图像构建器官或结构的分布外观模型和空间关系模型; 统计全身图集，包括一个或多个分布式外观模型和器官或结构的空间关系模型，在一个或多个全身成像模式中，由生成学习和建模模块构建; 以及构建用于执行器官，结构或疾病检测或分割中的至少一种的两类或多类分类器的辨别性学习和建模模块。

4. 发明授权

US08369593B2 Systems and methods for robust learning based annotation of medical radiographs 有权
标题翻译：用于健康学习的医学放射照片注释的系统和方法
公开(公告)号：US08369593B2
公开(公告)日：2013-02-05
申请号：US12787916
申请日：2010-05-26
申请人： Zhigang Peng , Yimo Tao , Xiang Sean Zhou , Yiqiang Zhan , Arun Krishnan
发明人： Zhigang Peng , Yimo Tao , Xiang Sean Zhou , Yiqiang Zhan , Arun Krishnan
IPC分类号： G06K9/00 , A61B6/00
CPC分类号： A61B6/032 , A61B6/469 , A61B6/488 , G06K9/3233 , G06K9/6231 , G06K9/6267 , G06K2209/05 , G06T7/12 , G06T7/73 , G06T2207/10081 , G06T2207/20104 , G06T2207/20164 , G06T2207/30048
摘要： Systems and methods for performing a medical imaging study include acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.
摘要翻译：用于执行医学成像研究的系统和方法包括获取初步扫描。从初步扫描中自动检测一组本地特征候选。使用其他本地特征候选者的多个组合来评估每个本地特征候选者的准确性，并且去除被评估为具有最低精度的局部特征候选。重复评估和去除步骤，直到仅保留预定数量的局部特征候选。感兴趣区域（ROI）基于剩余的预定数量的局部特征候选位于初步扫描内。基于初步扫描中ROI的位置执行医学成像研究。

5. 发明授权

US07087018B2 System and method for real-time feature sensitivity analysis based on contextual information 有权
标题翻译：基于情境信息的实时特征敏感性分析系统和方法
公开(公告)号：US07087018B2
公开(公告)日：2006-08-08
申请号：US10702984
申请日：2003-11-06
申请人： Dorin Comaniciu , Arun Krishnan , Xiang Sean Zhou , Bhavani Duggirala , Diane Paine
发明人： Dorin Comaniciu , Arun Krishnan , Xiang Sean Zhou , Bhavani Duggirala , Diane Paine
IPC分类号： A61B5/00 , A61B8/00
CPC分类号： A61B5/1075 , A61B8/02 , A61B8/065 , A61B8/0858 , A61B8/0883 , A61B8/463 , G06F19/00 , G06K9/623 , G06K9/6231 , G06K9/72 , G06K2209/051 , G16H40/63
摘要： A system and method for assigning feature sensitivity values to a set of potential measurements to be taken during a medical procedure of a patient in order to provide a medical diagnosis is disclosed. Data is received from a sensor that represents a particular medical measurement. The received data and context data are analyzed with respect to one or more sets of training models. Feature sensitivity values are derived for the particular medical measurement and other potential measurements to be taken based the analysis, and the feature sensitivity values are outputted.
摘要翻译：公开了一种用于将特征灵敏度值分配给患者的医疗过程中要采取的一组潜在测量以提供医学诊断的系统和方法。从代表特定医疗测量的传感器接收数据。相对于一组或多组训练模型分析所接收的数据和上下文数据。基于分析，针对特定医疗测量和其他可能的测量导出特征灵敏度值，并输出特征灵敏度值。

6. 发明申请

US20100284590A1 Systems and Methods for Robust Learning Based Annotation of Medical Radiographs 有权
标题翻译：用于健康学习的系统和方法基于医学影像学的注释
公开(公告)号：US20100284590A1
公开(公告)日：2010-11-11
申请号：US12787916
申请日：2010-05-26
申请人： Zhigang Peng , Yimo Tao , Xiang Sean Zhou , Yiqiang Zhan , Arun Krishnan
发明人： Zhigang Peng , Yimo Tao , Xiang Sean Zhou , Yiqiang Zhan , Arun Krishnan
IPC分类号： G06K9/46 , G06K9/00
CPC分类号： A61B6/032 , A61B6/469 , A61B6/488 , G06K9/3233 , G06K9/6231 , G06K9/6267 , G06K2209/05 , G06T7/12 , G06T7/73 , G06T2207/10081 , G06T2207/20104 , G06T2207/20164 , G06T2207/30048
摘要： Systems and methods for performing a medical imaging study include acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.
摘要翻译：用于执行医学成像研究的系统和方法包括获取初步扫描。从初步扫描中自动检测一组本地特征候选。使用其他本地特征候选者的多个组合来评估每个本地特征候选者的准确性，并且去除被评估为具有最低精度的局部特征候选。重复评估和去除步骤，直到仅保留预定数量的局部特征候选。感兴趣区域（ROI）基于剩余的预定数量的局部特征候选位于初步扫描内。基于初步扫描中ROI的位置执行医学成像研究。

7. 发明授权

US09020235B2 Systems and methods for viewing and analyzing anatomical structures 有权
标题翻译：用于观察和分析解剖结构的系统和方法
公开(公告)号：US09020235B2
公开(公告)日：2015-04-28
申请号：US13363753
申请日：2012-02-01
申请人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
发明人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
IPC分类号： G06K9/00 , A61B6/00 , A61B6/03 , G06F19/00 , G06T7/00 , A61B5/055 , A61B5/00
CPC分类号： A61B6/5217 , A61B5/055 , A61B5/4504 , A61B5/726 , A61B5/7425 , A61B5/743 , A61B5/7485 , A61B6/032 , A61B6/469 , A61B6/505 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T2207/10116
摘要： Systems and methods for supporting a diagnostic workflow from a computer system are disclosed herein. In accordance with one implementation, a set of pre-identified anatomical landmarks associated with one or more structures of interest within one or more medical images are presented to a user. In response to a user input selecting at least one or more regions of interest including one or more of the pre-identified anatomical landmarks, the user is automatically navigated to the selected region of interest. In another implementation, a second user input selecting one or more measurement tools is received. An evaluation may be automatically determined based on one or more of the set of anatomical landmarks in response to the second user input.
摘要翻译：本文公开了用于从计算机系统支持诊断工作流程的系统和方法。根据一个实施方案，向用户呈现与一个或多个医学图像内的一个或多个感兴趣结构相关联的一组预先识别的解剖学标记。响应于用户输入选择至少一个或多个感兴趣区域，包括预先识别的解剖标志中的一个或多个，用户被自动导航到所选择的感兴趣区域。在另一实现中，接收选择一个或多个测量工具的第二用户输入。响应于第二用户输入，可以基于该组解剖标志中的一个或多个来自动确定评估。

8. 发明授权

US08588495B2 Systems and methods for computer aided diagnosis and decision support in whole-body imaging 有权
标题翻译：全身成像计算机辅助诊断和决策支持的系统和方法
公开(公告)号：US08588495B2
公开(公告)日：2013-11-19
申请号：US12968492
申请日：2010-12-15
申请人： Alok Gupta , Arun Krishnan , Xiang Sean Zhou
发明人： Alok Gupta , Arun Krishnan , Xiang Sean Zhou
IPC分类号： G06K9/00 , A61B5/00 , A61B5/05 , G06Q10/00
CPC分类号： G06T7/0012 , G06F19/00 , G06F19/321 , G06T7/41 , G06T2207/10081 , G06T2207/10104 , G06T2207/20101 , G06T2207/30004 , G16H50/20
摘要： A system for providing automatic diagnosis and decision support includes: a medical image database; generative learning and modeling modules that build distributional appearance models and spatial relational models of organs or structures using images from the medical image database; a statistical whole-body atlas that includes one or more distributional appearance models and spatial relational models of organs or structure, in one or more whole-body imaging modalities, built by the generative learning and modeling modules; and discriminative learning and modeling modules that build two-class or multi-class classifiers for performing at least one of organ, structure or disease detection or segmentation.
摘要翻译：一种用于提供自动诊断和决策支持的系统包括：医学图像数据库; 生成学习和建模模块，使用医学图像数据库中的图像构建器官或结构的分布外观模型和空间关系模型; 统计全身图集，包括一个或多个分布式外观模型和器官或结构的空间关系模型，在一个或多个全身成像模式中，由生成学习和建模模块构建; 以及构建用于执行器官，结构或疾病检测或分割中的至少一种的两类或多类分类器的辨别性学习和建模模块。

9. 发明申请

US20120172700A1 Systems and Methods for Viewing and Analyzing Anatomical Structures 有权
标题翻译：观察和分析解剖结构的系统和方法
公开(公告)号：US20120172700A1
公开(公告)日：2012-07-05
申请号：US13363753
申请日：2012-02-01
申请人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
发明人： Arun Krishnan , Marcos Salganicoff , Xiang Sean Zhou , Venkat Raghavan Ramamurthy , Luca Bogoni , Gerardo Hermosillo Valadez
IPC分类号： A61B6/00 , G09G5/00
CPC分类号： A61B6/5217 , A61B5/055 , A61B5/4504 , A61B5/726 , A61B5/7425 , A61B5/743 , A61B5/7485 , A61B6/032 , A61B6/469 , A61B6/505 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T2207/10116
摘要： Systems and methods for supporting a diagnostic workflow from a computer system are disclosed herein. In accordance with one implementation, a set of pre-identified anatomical landmarks associated with one or more structures of interest within one or more medical images are presented to a user. In response to a user input selecting at least one or more regions of interest including one or more of the pre-identified anatomical landmarks, the user is automatically navigated to the selected region of interest. In another implementation, a second user input selecting one or more measurement tools is received. An evaluation may be automatically determined based on one or more of the set of anatomical landmarks in response to the second user input.
摘要翻译：本文公开了用于从计算机系统支持诊断工作流程的系统和方法。根据一个实施方案，向用户呈现与一个或多个医学图像内的一个或多个感兴趣结构相关联的一组预先识别的解剖学标记。响应于用户输入选择至少一个或多个感兴趣区域，包括预先识别的解剖标志中的一个或多个，用户被自动导航到所选择的感兴趣区域。在另一实现中，接收选择一个或多个测量工具的第二用户输入。响应于第二用户输入，可以基于该组解剖标志中的一个或多个来自动确定评估。

10. 发明授权

US08494235B2 Automatic detection of lymph nodes 有权
标题翻译：自动检测淋巴结
公开(公告)号：US08494235B2
公开(公告)日：2013-07-23
申请号：US12121865
申请日：2008-05-16
申请人： Senthil Periaswamy , Xiang Zhou , Yiqiang Zhan , Arun Krishnan
发明人： Senthil Periaswamy , Xiang Zhou , Yiqiang Zhan , Arun Krishnan
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T7/62 , G06T7/68 , G06T2207/30101
摘要： A method for detecting lymph nodes in a medical image includes receiving image data. One or more regions of interest are detected from within the received image data. One or more lymph node candidates are identified using a set of predefined parameters that is particular to the detected region of interest where each lymph node candidate is located. The identifying unit may identify the one or more lymph node candidates by performing DGFR processing. The method may also include receiving user-provided adjustments to the predefined parameters that are particular to the detected regions of interest and identifying the lymph node candidates based on the adjusted parameters. The lymph node candidates identified based on the adjusted parameters may be displayed along with the image data in real-time as the adjustments are provided.
摘要翻译：用于检测医学图像中的淋巴结的方法包括接收图像数据。从所接收的图像数据中检测一个或多个感兴趣的区域。使用一组预定义的参数来识别一个或多个淋巴结候选物，该组预定参数对于检测到的每个淋巴结候选者所在的感兴趣区域是特别的。识别单元可以通过执行DGFR处理来识别一个或多个淋巴结候选。该方法还可以包括接收用户提供的对所检测到的感兴趣区域特有的预定义参数的调整，并且基于经调整的参数来识别淋巴结候选。随着提供调整，可以实时地显示基于调整后的参数识别的淋巴结候选以及图像数据。

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