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1. 发明申请

WO2009020548A2 REDUCTION OF LYMPH TISSUE FALSE POSITIVES IN PULMONARY EMBOLISM DETECTION 审中-公开
标题翻译：肺栓塞假阳性在肺栓塞检测中的应用
公开(公告)号：WO2009020548A2
公开(公告)日：2009-02-12
申请号：PCT/US2008009239
申请日：2008-07-31
申请人： SIEMENS MEDICAL SOLUTIONS , GHANEM BERNARD SEMAAN , LIANG JIANMING , BI JINBO
发明人： GHANEM BERNARD SEMAAN , LIANG JIANMING , BI JINBO
IPC分类号： G06T7/00 , A61B5/00
CPC分类号： G06T7/0012 , G06T7/12 , G06T7/60 , G06T7/73 , G06T2207/10081 , G06T2207/30061 , G06T2207/30101
摘要： A system for automatically detecting pulmonary emboli from medical image data includes receiving image data (S101 ), automatically detecting one or more pulmonary embolism candidates from the image data (S 102), segmenting an airway tract from the image data (S 103), segmenting an artery structure from the image data (S 103), calculating a distance between each of the candidates and a nearest portion of the segmented airway (S 104), determining whether each of the candidates is within or outside of the segmented artery structure (S 105), rejecting candidates based on the calculated distance between each of the candidates and the nearest portion of the segmented airway and the determination as to whether each of the candidates is within or outside of the segmented artery structure (S 106), and indicating the location of the non-rejected candidates within the image data (S 107).
摘要翻译：一种用于从医学图像数据自动检测肺栓塞的系统包括：接收图像数据（S101）;从图像数据自动检测一个或多个肺栓塞候选物（S102）;从图像数据中分割气道（S103）;分割根据图像数据计算动脉结构（S103），计算每个候选者与分段气道的最近部分之间的距离（S104），确定每个候选者是否在分段动脉结构内（S 基于所计算的每个候选者与分段气道的最近部分之间的距离以及关于每个候选者是否在分段动脉结构之内或之外的确定来拒绝候选者（S106），并且指示未被拒绝的候选者在图像数据内的位置（S107）。

2. 发明申请

WO2006034366A1 HIERARCHICAL MEDICAL IMAGE VIEW DETERMINATION 审中-公开
标题翻译：分层医学图像检测
公开(公告)号：WO2006034366A1
公开(公告)日：2006-03-30
申请号：PCT/US2005/033876
申请日：2005-09-21
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , KRISHNAN, Sriram , BI, Jinbo , RAO, R., Bharat , STOECKEL, Jonathan , OTEY, Matthew, Eric
发明人： KRISHNAN, Sriram , BI, Jinbo , RAO, R., Bharat , STOECKEL, Jonathan , OTEY, Matthew, Eric
IPC分类号： G06K9/68 , G06T7/00
CPC分类号： G06T7/0012 , G06K9/6217 , G06K9/6282 , G06T2207/30048
摘要： A cardiac view of a medical ultrasound image is automatically identified (24, 26, 28). By grouping different views into sub-categories, a hierarchal classifier identifies the views. For example, apical views are distinguished (24) from parasternal views. Specific types of apical or parasternal views are identified (26, 28) based on distinguishing between images of the geneses. Different features are used for classifying, such as gradients, functions of the gradients, statistics of an average frame of data from a clip or sequence of frames, or a number of edges along a given direction. The number of features used may be compressed (22), such as by classifying a plurality of features into a new feature. For example, alpha weights in a model of features and classes are determined and used as features for classification
摘要翻译：自动识别医学超声图像的心脏视图（24,26,28）。通过将不同的视图分组到子类别中，层级分类器标识视图。例如，顶峰视图与胸骨旁观点（24）不同。基于区分基因图像，确定了顶端或胸骨旁观察的具体类型（26,28）。不同的特征用于分类，例如梯度，梯度的功能，来自剪辑或帧序列的平均数据帧的统计，或沿给定方向的多个边缘的统计。所使用的特征的数量可以被压缩（22），例如通过将多个特征分类为新特征。例如，确定特征和类的模型中的α权重并将其用作分类的特征

3. 发明申请

WO2008097520A2 SYSTEM AND METHOD FOR COMPUTER AIDED DETECTION OF PULMONARY EMBOLISM IN TOBOGGANING IN CT ANGIOGRAPHY 审中-公开
标题翻译：计算机辅助检测CT血管造影中肺动脉栓塞的系统与方法
公开(公告)号：WO2008097520A2
公开(公告)日：2008-08-14
申请号：PCT/US2008/001474
申请日：2008-02-04
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , LIANG, Jianming , BI, Jinbo
发明人： LIANG, Jianming , BI, Jinbo
IPC分类号： G06T7/00 , A61B6/03 , A61B6/12
CPC分类号： G06K9/00201 , G06T7/0012 , G06T7/11 , G06T2207/10081 , G06T2207/30061 , G06T2207/30101
摘要： A method for detecting pulmonary embolisms in computed tomographic (CT) angiography includes providing a digitized (CT) image acquired from inside a pulmonary vessel, the image comprising a plurality of intensities corresponding to a 3-dimensional grid of voxels, for each voxel in the image, extracting a first pulmonary embolism (PE) candidate and PE boundary from the voxel, and for each voxel in the PE boundary, selecting a voxel from the PE boundary, extracting a subsequent PE candidate and PE boundary from the voxel, merging the subsequent PE candidate with the first PE candidate, and merging the subsequent PE boundary with the first PE boundary.
摘要翻译：用于检测计算机断层摄影（CT）血管造影术中的肺栓塞的方法包括提供从肺容器内获得的数字化（CT）图像，该图像包括对应于体素的三维网格的多个强度，图像，从体素提取第一肺栓塞（PE）候选者和PE边界，并且对于PE边界中的每个体素，从PE边界中选择体素，从体素提取后续PE候选和PE边界，合并后续 PE候选人与第一个PE候选人，并将后续PE边界与第一个PE边界合并。

4. 发明申请

WO2006132975A1 SYSTEM AND METHOD FOR LEARNING RANKINGS VIA CONVEX HULL SEPARATION 审中-公开
标题翻译：通过凸轮分离学习排名的系统和方法
公开(公告)号：WO2006132975A1
公开(公告)日：2006-12-14
申请号：PCT/US2006/021475
申请日：2006-06-02
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , BI, Jinbo , FUNG, Glenn , KRISHNAN, Sriram , KRISHNAPURAM, Balaji , RAO, R. Bharat , ROSALES, Romer, E.
发明人： BI, Jinbo , FUNG, Glenn , KRISHNAN, Sriram , KRISHNAPURAM, Balaji , RAO, R. Bharat , ROSALES, Romer, E.
IPC分类号： G06K9/00
CPC分类号： G06K9/6269
摘要： A method for finding a ranking function /that classifies feature points in an n- dimensional space includes providing (61) a plurality of feature points Xk derived from tissue sample regions in a digital medical image, providing (62) training data A comprising training samples A j where formula (I), providing (63) an ordering E = {( P,Q )| A P A Q } of at least some training data sets where all training samples x I ∈ A p are ranked higher than any sample x j ∈ A Q , and solving (64) a mathematical optimization program to determine the ranking function f that classifies said feature points x into sets A . For any two sets A i , A j , A i - A j , and the ranking function f satisfies inequality constraints f ( x i ) ≤ f ( x j ) for all x I ∈ conv(A i ) and x j ∈ conv (A j ) , where conv ( A ) represents the convex hull of the elements of set A .
摘要翻译：一种用于寻找在第n维空间中对特征点进行分类的分级功能的方法包括提供（61）从数字医学图像中的组织样本区域导出的多个特征点X k，提供（62）包括训练样本的训练数据A 一个

5. 发明申请

WO2005122066A1 SUPPORT VECTOR CLASSIFICATION WITH BOUNDED UNCERTAINTIES IN INPUT DATA 审中-公开
标题翻译：支持向量分类与输入数据中的边界不确定性
公开(公告)号：WO2005122066A1
公开(公告)日：2005-12-22
申请号：PCT/US2005/019416
申请日：2005-06-02
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , BI, Jinbo
发明人： BI, Jinbo
IPC分类号： G06K9/62
CPC分类号： G06K9/6269
摘要： A computer-implemented method for determining a boundary for binary classification includes providing a data set, initializing a value for noise in the data set (401), and determining a hyperplane dividing the data set and a slack variable given a current value for noise (402). The method further includes updating the value for noise and the slack variable given the hyperplane (403), and determining the hyperplane to be the boundary for binary classification of the data set upon determining a termination criterion to be met (404), wherein elements of the data set are classified according to the boundary.
摘要翻译：用于确定用于二进制分类的边界的计算机实现的方法包括提供数据集，初始化数据集（401）中的噪声的值，以及确定分割数据集的超平面和给定噪声的当前值的松弛变量（ 402）。该方法还包括更新噪声值和给定超平面（403）的松弛变量，以及在确定要满足的终止标准（404）时，将超平面确定为数据集二进制分类的边界（404），其中元素数据集根据边界进行分类。

6. 发明申请

WO2005078638A3 A SYSTEM AND METHOD FOR A SPARSE KERNEL EXPANSION FOR A BAYES CLASSIFIER 审中-公开
标题翻译：一种用于贝叶类分类器的小型扩展的系统和方法
公开(公告)号：WO2005078638A3
公开(公告)日：2005-10-06
申请号：PCT/US2005003806
申请日：2005-02-04
申请人： SIEMENS MEDICAL SOLUTIONS , DUNDAR MURAT , FUNG GLENN , BI JINBO , RAO R BHARAT
发明人： DUNDAR MURAT , FUNG GLENN , BI JINBO , RAO R BHARAT
IPC分类号： G06K9/62
CPC分类号： G06K9/6256
摘要： A method and device having instructions for analyzing input data-space by learning classifiers include choosing a candidate subset from a predetermined training data-set that is used to analyze the input data-space. Candidates are temporarily added from the candidate subset to an expansion set to generate a new kernel space for the input data-space by predetermined repeated evaluations of leave-one-out errors for the candidates added to the expansion set. This is followed by removing the candidates temporarily added to the expansion set after the leave-one-out error evaluations are performed, and selecting the candidates to be permanently added to the expansion set based on the leave-one-out errors of the candidates temporarily added to the expansion set to determine the one or more classifiers
摘要翻译：具有用于通过学习分类器分析输入数据空间的指令的方法和设备包括从用于分析输入数据空间的预定训练数据集中选择候选子集。将候选者从候选子集临时添加到扩展集合，以通过对添加到扩展集合的候选者的一对一错误进行预先重复的评估来为输入数据空间生成新的内核空间。之后，在执行一次性错误评估之后，删除临时添加到扩展集的候选者，并且基于临时的候选者的一次性错误选择要永久添加到扩展集的候选项添加到扩展集以确定一个或多个分类器

7. 发明申请

WO2009020548A3 REDUCTION OF LYMPH TISSUE FALSE POSITIVES IN PULMONARY EMBOLISM DETECTION 审中-公开
公开(公告)号：WO2009020548A3
公开(公告)日：2009-02-12
申请号：PCT/US2008/009239
申请日：2008-07-31
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , GHANEM, Bernard, Semaan , LIANG, Jianming , BI, Jinbo
发明人： GHANEM, Bernard, Semaan , LIANG, Jianming , BI, Jinbo
IPC分类号： G06T7/00
摘要： A system for automatically detecting pulmonary emboli from medical image data includes receiving image data (S101 ), automatically detecting one or more pulmonary embolism candidates from the image data (S 102), segmenting an airway tract from the image data (S 103), segmenting an artery structure from the image data (S 103), calculating a distance between each of the candidates and a nearest portion of the segmented airway (S 104), determining whether each of the candidates is within or outside of the segmented artery structure (S 105), rejecting candidates based on the calculated distance between each of the candidates and the nearest portion of the segmented airway and the determination as to whether each of the candidates is within or outside of the segmented artery structure (S 106), and indicating the location of the non-rejected candidates within the image data (S 107).

8. 发明申请

WO2005078638A2 A SYSTEM AND METHOD FOR A SPARSE KERNEL EXPANSION FOR A BAYES CLASSIFIER 审中-公开
标题翻译：一种用于贝叶斯分类器的稀疏核展开的系统和方法
公开(公告)号：WO2005078638A2
公开(公告)日：2005-08-25
申请号：PCT/US2005/003806
申请日：2005-02-04
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , DUNDAR, Murat , FUNG, Glenn , BI, Jinbo , RAO, R. Bharat
发明人： DUNDAR, Murat , FUNG, Glenn , BI, Jinbo , RAO, R. Bharat
IPC分类号： G06K9/62
CPC分类号： G06K9/6256
摘要： A method and device having instructions for analyzing input data-space by learning classifiers include choosing a candidate subset from a predetermined training data-set that is used to analyze the input data-space. Candidates are temporarily added from the candidate subset to an expansion set to generate a new kernel space for the input data-space by predetermined repeated evaluations of leave-one-out errors for the candidates added to the expansion set. This is followed by removing the candidates temporarily added to the expansion set after the leave-one-out error evaluations are performed, and selecting the candidates to be permanently added to the expansion set based on the leave-one-out errors of the candidates temporarily added to the expansion set to determine the one or more classifiers
摘要翻译：具有用于通过学习分类器来分析输入数据空间的指令的方法和设备包括从用于分析输入数据空间的预定训练数据集中选择候选子集。从候选子集临时将候选者添加到扩展集以通过对添加到扩展集的候选者的预留重复评估来为输入数据空间生成新的内核空间。之后，在执行留一错误评估之后，删除临时添加到扩展集的候选项，并基于候选项的临时一错误选择要永久添加到扩展集的候选项添加到扩展集以确定一个或多个分类器

9. 发明申请

WO2005078631A1 HIERARCHICAL MODELING IN MEDICAL ABNORMALITY DETECTION 审中-公开
标题翻译：医学异常检测中的分层建模
公开(公告)号：WO2005078631A1
公开(公告)日：2005-08-25
申请号：PCT/US2005/004188
申请日：2005-02-09
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , KRISHNAN, Sriram , BI, Jinbo , RAO, R. Bharat
发明人： KRISHNAN, Sriram , BI, Jinbo , RAO, R. Bharat
IPC分类号： G06F19/00
CPC分类号： G16H50/20 , G06F19/00 , G16H50/50
摘要： Hierarchal modeling is used to distinguish one state (26, 28, 32, 34, 38, 40, 44, 46) or class from three or more classes. In a first stage, a normal (26) or other class is distinguished from a diseased (28) or other groups of classes. If the results of the first stage classification indicate diseased (28) or data within the groups of different classes, a subsequent stage of classification is performed. In a subsequent stage of classification, the data is classified to distinguish one or more other classes (32, 34, 38, 40, 44, 46) from the remaining classes. Using two or more stages, medical information is classified by eliminating one or more possible classes in each stage to finally identify a particular class (26, 28, 32, 34, 38, 40, 44, 46) most appropriate or probable for the data.
摘要翻译：分层建模用于将一个状态（26,28,32,34,38,40,44,46）或类与三个或更多个类别区分开。在第一阶段，正常（26）或其他类别与患病（28）或其他类别的组不同。如果第一阶段分类的结果表示患病（28）或不同类别的组内的数据，则进行后续分类阶段。在分类的后续阶段，数据被分类以区分一个或多个其他类别（32,34,38,40,44,46）与其余类别。使用两个或更多个阶段，通过消除每个阶段中的一个或多个可能的类别来分类医学信息，以最终确定最合适或可能的数据的特定类别（26,28,34,34,38,40,44,46）。

10. 发明申请

WO2008097520A3 SYSTEM AND METHOD FOR COMPUTER AIDED DETECTION OF PULMONARY EMBOLISM IN TOBOGGANING IN CT ANGIOGRAPHY 审中-公开
标题翻译：计算机辅助检测CT血管造影中肺动脉栓塞的系统与方法
公开(公告)号：WO2008097520A3
公开(公告)日：2009-06-04
申请号：PCT/US2008001474
申请日：2008-02-04
申请人： SIEMENS MEDICAL SOLUTIONS , LIANG JIANMING , BI JINBO
发明人： LIANG JIANMING , BI JINBO
IPC分类号： G06T7/00 , A61B6/03 , G06K9/00
CPC分类号： G06K9/00201 , G06T7/0012 , G06T7/11 , G06T2207/10081 , G06T2207/30061 , G06T2207/30101
摘要： A method for detecting pulmonary embolisms in computed tomographic (CT) angiography includes providing a digitized (CT) image acquired from inside a pulmonary vessel, the image comprising a plurality of intensities corresponding to a 3-dimensional grid of voxels, for each voxel in the image, extracting a first pulmonary embolism (PE) candidate and PE boundary from the voxel, and for each voxel in the PE boundary, selecting a voxel from the PE boundary, extracting a subsequent PE candidate and PE boundary from the voxel, merging the subsequent PE candidate with the first PE candidate, and merging the subsequent PE boundary with the first PE boundary.
摘要翻译：用于检测计算机断层摄影（CT）血管造影术中的肺栓塞的方法包括提供从肺容器内获得的数字化（CT）图像，该图像包括对应于体素的三维网格的多个强度，图像，从体素提取第一肺栓塞（PE）候选者和PE边界，并且对于PE边界中的每个体素，从PE边界中选择体素，从体素提取后续PE候选和PE边界，合并后续 PE候选人与第一个PE候选人，并将后续PE边界与第一个PE边界合并。

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