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1.发明授权System and method for real-time feature sensitivity analysis based on contextual information 有权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
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。
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2.发明授权公开(公告)号：US07458936B2
公开(公告)日：2008-12-02
申请号：US10703024
申请日：2003-11-06
申请人： Xiang Sean Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
发明人： Xiang Sean Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
IPC分类号： A61B8/00
CPC分类号： G06K9/6276 , A61B8/0883 , G06F19/00 , G06K9/6256 , G06K2209/05 , G06Q50/22 , G16H50/20 , Y10S128/92 , Y10S128/924
摘要： A system and method for providing decision support to a physician during a medical examination is disclosed. Data is received from a sensor representing a particular medical measurement. The received data includes image data. The received data and context data is analyzed with respect to one or more sets of training models. Probability values for the particular medical measurement and other measurements to be taken are derived based on the analysis and based on identified classes. The received image data is compared with training images. Distance values are determined between the received image data and the training images, and the training images are associated with the identified classes. Absolute value feature sensitivity scores are derived for the particular medical measurement and other measurements to be taken based on the analysis. The probability values, distance values and absolute value feature sensitivity scores are outputted to the user.
摘要翻译： 公开了一种用于在医学检查期间向医师提供决策支持的系统和方法。 从代表特定医疗测量的传感器接收数据。 所接收的数据包括图像数据。 相对于一组或多组训练模型分析接收到的数据和上下文数据。 特定医疗测量和其他测量的概率值基于分析并基于识别的类别导出。 将接收到的图像数据与训练图像进行比较。 在接收的图像数据和训练图像之间确定距离值，并且训练图像与所识别的类别相关联。 基于分析，针对特定医疗测量和其他测量得出绝对值特征灵敏度得分。 将概率值，距离值和绝对值特征灵敏度得分输出给用户。
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3.发明申请公开(公告)号：US20090080732A1
公开(公告)日：2009-03-26
申请号：US12243199
申请日：2008-10-01
申请人： Xiang Sean Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
发明人： Xiang Sean Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
CPC分类号： G06K9/6276 , A61B8/0883 , G06F19/00 , G06K9/6256 , G06K2209/05 , G06Q50/22 , G16H50/20 , Y10S128/92 , Y10S128/924
摘要： A system and method for providing decision support to a physician during a medical examination is disclosed. Data is received from a sensor representing a particular medical measurement. The received data includes image data. The received data and context data is analyzed with respect to one or more sets of training models. Probability values for the particular medical measurement and other measurements to be taken are derived based on the analysis and based on identified classes. The received image data is compared with training images. Distance values are determined between the received image data and the training images, and the training images are associated with the identified classes. Absolute value feature sensitivity scores are derived for the particular medical measurement and other measurements to be taken based on the analysis. The probability values, distance values and absolute value feature sensitivity scores are outputted to the user.
摘要翻译： 公开了一种用于在医学检查期间向医师提供决策支持的系统和方法。 从代表特定医疗测量的传感器接收数据。 所接收的数据包括图像数据。 相对于一组或多组训练模型分析接收到的数据和上下文数据。 特定医疗测量和其他测量的概率值基于分析并基于识别的类别导出。 将接收到的图像数据与训练图像进行比较。 在接收的图像数据和训练图像之间确定距离值，并且训练图像与所识别的类别相关联。 基于分析，针对特定医疗测量和其他测量得出绝对值特征灵敏度得分。 将概率值，距离值和绝对值特征灵敏度得分输出给用户。
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4.发明授权公开(公告)号：US08060178B2
公开(公告)日：2011-11-15
申请号：US12243199
申请日：2008-10-01
申请人： Xiang Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
发明人： Xiang Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
IPC分类号： A61B5/00
CPC分类号： G06K9/6276 , A61B8/0883 , G06F19/00 , G06K9/6256 , G06K2209/05 , G06Q50/22 , G16H50/20 , Y10S128/92 , Y10S128/924
摘要： A system and method for providing decision support to a physician during a medical examination is disclosed. Data is received from a sensor representing a particular medical measurement. The received data includes image data. The received data and context data is analyzed with respect to one or more sets of training models. Probability values for the particular medical measurement and other measurements to be taken are derived based on the analysis and based on identified classes. The received image data is compared with training images. Distance values are determined between the received image data and the training images, and the training images are associated with the identified classes. Absolute value feature sensitivity scores are derived for the particular medical measurement and other measurements to be taken based on the analysis. The probability values, distance values and absolute value feature sensitivity scores are outputted to the user.
摘要翻译： 公开了一种用于在医学检查期间向医师提供决策支持的系统和方法。 从代表特定医疗测量的传感器接收数据。 所接收的数据包括图像数据。 相对于一组或多组训练模型分析接收到的数据和上下文数据。 特定医疗测量和其他测量的概率值基于分析并基于识别的类别导出。 将接收到的图像数据与训练图像进行比较。 在接收的图像数据和训练图像之间确定距离值，并且训练图像与所识别的类别相关联。 基于分析，针对特定医疗测量和其他测量得出绝对值特征灵敏度得分。 将概率值，距离值和绝对值特征灵敏度得分输出给用户。
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公开(公告)号：US07244230B2
公开(公告)日：2007-07-17
申请号：US10702721
申请日：2003-11-06
CPC分类号： A61B8/56 , A61B8/00 , A61B8/4427 , A61B8/485 , A61B8/565 , G06F19/00 , G06T7/0012 , G06T2207/30004 , G16H50/20 , Y02A90/22 , Y02A90/26 , Y10S128/925
摘要： Various attributes for medical CAD analysis used alone or in combination are disclosed, including: (1) using medical sensor data and context information associated with the configuration of the medical system to provide recommendations for further acts to be performed for more accurate or different diagnosis, (2) recommending further acts to be performed and providing an indication of the importance of the further act for further diagnosis, (3) distributing the computer-assisted diagnosis software and/or database over multiple systems, and (4) transmitting patient data to a remote system for CAD diagnosis and using the results of the CAD diagnosis at the remote facility.
摘要翻译： 公开了用于单独或组合使用的医疗CAD分析的各种属性，包括：（1）使用与医疗系统的配置相关联的医疗传感器数据和上下文信息来提供用于执行更准确或不同诊断的进一步行为的建议， （2）推荐进一步的行为，并提供进一步诊断的进一步行动的重要性的指示，（3）通过多个系统分发计算机辅助诊断软件和/或数据库，以及（4）将患者数据发送到 用于CAD诊断的远程系统，并在远程设施中使用CAD诊断的结果。
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6.发明授权Systems and methods for automated diagnosis and decision support for heart related diseases and conditions 有权用于心脏相关疾病和病症的自动诊断和决策支持的系统和方法公开(公告)号：US07912528B2
公开(公告)日：2011-03-22
申请号：US10876801
申请日：2004-06-25
申请人： Sriram Krishnan , Alok Gupta , R. Bharat Rao , Dorin Comaniciu , Xiang Sean Zhou
发明人： Sriram Krishnan , Alok Gupta , R. Bharat Rao , Dorin Comaniciu , Xiang Sean Zhou
IPC分类号： A61B5/05
摘要： CAD (computer-aided diagnosis) systems and applications for cardiac imaging are provided, which implement methods to automatically extract and analyze features from a collection of patient information (including image data and/or non-image data) of a subject patient, to provide decision support for various aspects of physician workflow including, for example, automated assessment of regional myocardial function through wall motion analysis, automated diagnosis of heart diseases and conditions such as cardiomyopathy, coronary artery disease and other heart-related medical conditions, and other automated decision support functions. The CAD systems implement machine-learning techniques that use a set of training data obtained (learned) from a database of labeled patient cases in one or more relevant clinical domains and/or expert interpretations of such data to enable the CAD systems to “learn” to analyze patient data and make proper diagnostic assessments and decisions for assisting physician workflow.
摘要翻译： 提供了用于心脏成像的CAD（计算机辅助诊断）系统和应用，其实现了从受试患者的患者信息（包括图像数据和/或非图像数据）的集合中自动提取和分析特征的方法，以提供 对医师工作流程的各个方面的决策支持，包括例如通过壁运动分析自动评估区域性心肌功能，心脏病的自动诊断和诸如心肌病，冠状动脉疾病和其他与心脏相关的医疗状况等条件，以及其他自动化决策 支持功能。 CAD系统实施机器学习技术，其使用从一个或多个相关临床领域的标记的患者病例的数据库获得（学习）的一组训练数据和/或对这些数据的专家解释，使得CAD系统能够“学习” 分析患者数据，进行适当的诊断评估和决策，以协助医师的工作流程。
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公开(公告)号：US07558402B2
公开(公告)日：2009-07-07
申请号：US10794476
申请日：2004-03-05
CPC分类号： G06K9/6247 , G06K9/3216 , G06K9/629 , G06K2209/051 , G06T7/215 , G06T7/251 , G06T2207/10132 , G06T2207/30048
摘要： A system and method for tracking a global shape of an object in motion is disclosed. One or more control points along an initial contour of the global shape are defined. Each of the one or more control points is tracked as the object is in motion. Uncertainty of a location of a control point in motion is represented using a number of techniques. The uncertainty to constrain the global shape is exploited using a prior shape model. In an alternative embodiment, multiple appearance models are built for each control point and the motion vectors produced by each model are combined in order to track the shape of the object. The movement of the shape of the object can be visually tracked using a display and color vectors.
摘要翻译： 公开了一种跟踪运动对象的全局形状的系统和方法。 定义沿着全局形状初始轮廓的一个或多个控制点。 一个或多个控制点中的每一个在物体运动时被跟踪。 使用许多技术来表示控制点在运动中的位置的不确定性。 使用先前的形状模型来利用限制全局形状的不确定性。 在替代实施例中，为每个控制点构建多个外观模型，并且组合由每个模型产生的运动矢量以跟踪对象的形状。 可以使用显示和颜色向量来可视地跟踪对象的形状的移动。
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8.发明授权System and method for detecting and matching anatomical structures using appearance and shape 有权使用外观和形状检测和匹配解剖结构的系统和方法公开(公告)号：US07536044B2
公开(公告)日：2009-05-19
申请号：US10991933
申请日：2004-11-18
CPC分类号： G06K9/6206 , G06K9/6256 , G06T7/12 , G06T7/149 , G06T7/251 , G06T2207/10132 , G06T2207/30048
摘要： A detection framework that matches anatomical structures using appearance and shape is disclosed. A training set of images are used in which object shapes or structures are annotated in the images. A second training set of images represents negative examples for such shapes and structures, i.e., images containing no such objects or structures. A classification algorithm trained on the training sets is used to detect a structure at its location. The structure is matched to a counterpart in the training set that can provide details about the structure's shape and appearance.
摘要翻译： 公开了一种使用外观和形状匹配解剖结构的检测框架。 使用图像的训练集，其中在图像中注释对象形状或结构。 图像的第二训练集表示这种形状和结构的负面例子，即不包含这样的对象或结构的图像。 训练集训练的分类算法用于检测其位置的结构。 该结构与训练集中的对应物匹配，可以提供关于结构形状和外观的细节。
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9.发明授权System and method for sequential kernel density approximation through mode propagation 有权通过模式传播进行顺序核密度近似的系统和方法公开(公告)号：US07480079B2
公开(公告)日：2009-01-20
申请号：US10936607
申请日：2004-09-08
申请人： Bohyung Han , Dorin Comaniciu , Ying Zhu , Xiang Sean Zhou
发明人： Bohyung Han , Dorin Comaniciu , Ying Zhu , Xiang Sean Zhou
CPC分类号： G06K9/6226 , G06F17/18 , G06T7/44
摘要： A system and method for sequential kernel density approximation uses mode propagation to determine mode locations by the mean-shift method and reduce the generated modes. Hessians are calculated corresponding to the mode locations to determine the covariance. Density is approximated to update the density function depending on whether the Hessian is a negative indefinite.
摘要翻译： 用于顺序核密度近似的系统和方法使用模式传播来通过平均移位方法确定模式位置并减少生成的模式。 对应于模式位置计算Hessians以确定协方差。 近似密度来更新密度函数，取决于黑森西是否是负不确定的。
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公开(公告)号：US07894647B2
公开(公告)日：2011-02-22
申请号：US11154349
申请日：2005-06-16
申请人： Xiang Sean Zhou , Dorin Comaniciu , Luca Bogoni
发明人： Xiang Sean Zhou , Dorin Comaniciu , Luca Bogoni
IPC分类号： G06K9/00
CPC分类号： G06K9/3216 , G06K9/6209 , G06K2209/051 , G06T7/11 , G06T7/12 , G06T2207/10072 , G06T2207/20081 , G06T2207/30028
摘要： A method for three-dimensional contour tracking includes building a plurality of shape models, building a plurality of appearance models, training a learning/classification algorithm using said shape models and appearance models, localizing a contour using the said learning/classification algorithm about an object in a digitized image, and tracking said contour along said object in 3D incorporating said learning/classification algorithm.
摘要翻译： 一种用于三维轮廓跟踪的方法包括建立多个形状模型，构建多个外观模型，使用所述形状模型和外观模型训练学习/分类算法，使用关于对象的所述学习/分类算法来定位轮廓 在数字化图像中，并且沿3D结合所述学习/分类算法的3D跟踪所述轮廓。
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