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1.发明授权Biological unit segmentation with ranking based on similarity applying a geometric shape and scale model 有权基于相似度的生物单位分割与应用几何形状和尺度模型公开(公告)号：US09589360B2
公开(公告)日：2017-03-07
申请号：US13666343
申请日：2012-11-01
Applicant: General Electric Company
Inventor： Yuchi Huang , Alberto Santamaria-Pang , Jens Rittscher
CPC classification number: G06T7/155 , G06K9/0014 , G06K9/44 , G06T7/11 , G06T2207/10056 , G06T2207/20016 , G06T2207/20036 , G06T2207/20152 , G06T2207/30024
Abstract: Embodiments of the disclosure are directed to segmenting a digital image of biological tissue into biological units, such as cells. A first weak or data driven segmentation is generated using image data representing the digital image to segment the digital image into a first set of biological units. Applying a geometric model, each unit in the first set of biological units is ranked based on a similarity in shape and scale between the unit and one or more other units in the image. A subset of units from the first set of biological units is selected based on the rank of each biological unit relative to a predetermined threshold rank. A second weak or data driven segmentation may then be generated using image data including the subset of biological units to segment that portion of the digital image into a second set of biological units.
Abstract translation: 本公开的实施例涉及将生物组织的数字图像分割成诸如细胞的生物单元。 使用表示数字图像的图像数据来生成第一弱或数据驱动的分割，以将数字图像分割成第一组生物单元。 应用几何模型，基于图像中的单元和一个或多个其他单元之间的形状和尺度的相似性对第一组生物单元中的每个单元进行排序。 基于每个生物单元相对于预定阈值秩的等级来选择来自第一组生物单元的单元的子集。 然后可以使用包括生物单元的子集的图像数据来生成第二弱或数据驱动的分割，以将数字图像的该部分分割成第二组生物单元。
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公开(公告)号：US20150310604A1
公开(公告)日：2015-10-29
申请号：US14260624
申请日：2014-04-24
Applicant: General Electric Company
Inventor： Ser Nam Lim , Jose Abiel Garza , David Scott Diwinsky , Li Guan , Shubao Liu , Xingwei Yang , Jens Rittscher
CPC classification number: G06T7/0004 , G01N2021/8896 , G06K9/52 , G06T7/001 , G06T7/80 , G06T17/00 , G06T19/00 , G06T2200/24 , G06T2207/30164 , G06T2207/30204 , G06T2219/012 , H04N17/00
Abstract: A method for image based inspection of an object includes receiving an image of an object from an image capture device, wherein the image includes a representation of the object with mil-level precision. The method further includes projecting a measurement feature of the object from the image onto a three-dimensional (3D) model of the object based on a final projection matrix; determining a difference between the projected measurement feature and an existing measurement feature on the 3D model; and sending a notification including the difference between the projected measurement feature and the existing measurement feature.
Abstract translation: 一种用于对对象进行图像检查的方法包括从图像捕获装置接收对象的图像，其中所述图像包括具有密度级精度的对象的表示。 所述方法还包括基于最终投影矩阵将所述对象的测量特征从所述图像投影到所述对象的三维（3D）模型上; 确定投影测量特征与3D模型上现有测量特征之间的差异; 并发送包括预测测量特征与现有测量特征之间的差异的通知。
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3.发明授权System and method for multiplexed biomarker quantitation using single cell segmentation on sequentially stained tissue 有权使用单次细胞分割在连续染色的组织上进行复合生物标志物定量的系统和方法公开(公告)号：US08995740B2
公开(公告)日：2015-03-31
申请号：US13865036
申请日：2013-04-17
Applicant: General Electric Company
Inventor： Alberto Santamaria-Pang , Jens Rittscher , Dirk Padfield , Ali Can , Zhengyu Pang , Musodiq Bello , Fiona Ginty , Christopher Sevinsky , Qing Li , Megan Rothney , Brion Sarachan
IPC: G06K9/00 , G06T7/00 , G01N33/574
CPC classification number: G06K9/0014 , G06T7/0012 , G06T2207/10064 , G06T2207/30024
Abstract: Improved systems and methods for the analysis of digital images are provided. More particularly, the present disclosure provides for improved systems and methods for the analysis of digital images of biological tissue samples. Exemplary embodiments provide for: i) segmenting, ii) grouping, and iii) quantifying molecular protein profiles of individual cells in terms of sub cellular compartments (nuclei, membrane, and cytoplasm). The systems and methods of the present disclosure advantageously perform tissue segmentation at the sub-cellular level to facilitate analyzing, grouping and quantifying protein expression profiles of tissue in tissue sections globally and/or locally. Performing local-global tissue analysis and protein quantification advantageously enables correlation of spatial and molecular configuration of cells with molecular information of different types of cancer.
Abstract translation: 提供了改进的数字图像分析系统和方法。 更具体地，本公开提供了用于分析生物组织样本的数字图像的改进的系统和方法。 示例性实施方案提供：i）分段，ii）分组，和iii）根据亚细胞区室（细胞核，膜和细胞质）量化各细胞的分子蛋白质谱。 本公开的系统和方法有利地在亚细胞水平进行组织分割，以便于全局和/或局部地分析，分组和定量组织部位中组织的蛋白质表达谱。 进行局部全局组织分析和蛋白质定量有利于使细胞的空间和分子构型与不同类型癌症的分子信息的相关性。
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公开(公告)号：US20140278115A1
公开(公告)日：2014-09-18
申请号：US14145099
申请日：2013-12-31
Inventor： Erhan Bas , Gianni Matteucci , Ali Can , Jens Rittscher , Weina Ge , Kelly E. Wrobel , Matthias G. Imhof , Leslie A. Wahrmund , Antonio Rafael da Costa Paiva
IPC: G01V1/30
CPC classification number: G01V1/30 , G01V1/301 , G01V99/005 , G01V2210/64
Abstract: A workflow is presented that facilitates defining geocontextual information as a set of rules for multiple seismic attributes. Modeling algorithms may be employed that facilitate analysis of multiple seismic attributes to find candidate regions that are most likely to satisfy the set of rules. These candidates may then be sorted based on how well they represent the geocontextual information.
Abstract translation: 提出了一种有助于将地理信息信息定义为多个地震属性的一组规则的工作流程。 可以采用促进多个地震属性分析的建模算法，以找到最有可能满足该组规则的候选区域。 然后，这些候选人可以根据它们代表地理文本信息的程度进行排序。
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公开(公告)号：US20140112557A1
公开(公告)日：2014-04-24
申请号：US13657255
申请日：2012-10-22
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Alberto Santamaria-Pang , Yuchi Huang , Jens Rittscher
IPC: G06K9/34
CPC classification number: G06K9/34 , G06K9/00147 , G06T7/0012 , G06T7/12 , G06T2207/10056 , G06T2207/20016 , G06T2207/20036 , G06T2207/20072 , G06T2207/20076 , G06T2207/20081 , G06T2207/20152 , G06T2207/30024
Abstract: A method of segmenting a digital image of biological tissue includes accessing a ranking model calculated from training data representing shapes of conforming and non-conforming biological unit exemplars. The ranking model may include support vectors defining a hyperplane in a vector space. The method further includes accessing image data representing the digital image, identifying a first shape and a set of second constituent shapes in the digital image, wherein the first shape comprises a union of the set of second constituent shapes, determining a rank of a first data point in the image data corresponding to the first shape and a rank of a second data point in the image data corresponding to the set of second constituent shapes into the vector space, and segmenting the digital image using the first shape or the set of second constituent shapes based on which data point has a greater respective rank.
Abstract translation: 分割生物组织的数字图像的方法包括访问由表示符合和不符合生物单元样本的形状的训练数据计算的排名模型。 排名模型可以包括在向量空间中定义超平面的支持向量。 该方法还包括访问表示数字图像的图像数据，识别数字图像中的第一形状和一组第二组成形状，其中第一形状包括该组第二组成形状的并集，确定第一数据的等级 将与第一形状相对应的图像数据和对应于该组第二构成形状的图像数据中的第二数据点的等级排列成向量空间，并且使用第一形状或一组第二成分分割数字图像 基于哪个数据点具有更大的相应等级的形状。
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Patent Agency Ranking
公开(公告)号：US09952340B2
公开(公告)日：2018-04-24
申请号：US14145099
申请日：2013-12-31
Inventor： Erhan Bas , Gianni Matteucci , Ali Can , Jens Rittscher , Weina Ge , Kelly E. Wrobel , Matthias G. Imhof , Leslie A. Wahrmund , Antonio Rafael da Costa Paiva
CPC classification number: G01V1/30 , G01V1/301 , G01V99/005 , G01V2210/64
Abstract: A workflow is presented that facilitates defining geocontextual information as a set of rules for multiple seismic attributes. Modeling algorithms may be employed that facilitate analysis of multiple seismic attributes to find candidate regions that are most likely to satisfy the set of rules. These candidates may then be sorted based on how well they represent the geocontextual information.
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公开(公告)号：US09297918B2
公开(公告)日：2016-03-29
申请号：US13729769
申请日：2012-12-28
Applicant: General Electric Company
Inventor： Ser Nam Lim , John Robert Hare , Jens Rittscher , Jie Yu , Ya Xue
CPC classification number: G06N99/005 , G01V1/301 , G01V99/00 , G01V2210/64
Abstract: An approach for seismic data analysis is provided. In accordance with various embodiments, the active learning approaches are employed in conjunction with an analysis algorithm that is used to process the seismic data. Algorithms that may employ such active learning include, but are not limited to, ranking algorithms and classification algorithms.
Abstract translation: 提供了一种地震数据分析方法。 根据各种实施例，主动学习方法与用于处理地震数据的分析算法结合使用。 可以采用这种主动学习的算法包括但不限于排序算法和分类算法。
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公开(公告)号：US20140188769A1
公开(公告)日：2014-07-03
申请号：US13729769
申请日：2012-12-28
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Ser Nam Lim , John Robert Hare , Jens Rittscher , Jie Yu , Ya Xue
IPC: G06N99/00
CPC classification number: G06N99/005 , G01V1/301 , G01V99/00 , G01V2210/64
Abstract: An approach for seismic data analysis is provided. In accordance with various embodiments, the active learning approaches are employed in conjunction with an analysis algorithm that is used to process the seismic data. Algorithms that may employ such active learning include, but are not limited to, ranking algorithms and classification algorithms.
Abstract translation: 提供了一种地震数据分析方法。 根据各种实施例，主动学习方法与用于处理地震数据的分析算法结合使用。 可以采用这种主动学习的算法包括但不限于排序算法和分类算法。
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公开(公告)号：US08908945B2
公开(公告)日：2014-12-09
申请号：US13657255
申请日：2012-10-22
Applicant: General Electric Company
Inventor： Alberto Santamaria-Pang , Yuchi Huang , Jens Rittscher
CPC classification number: G06K9/34 , G06K9/00147 , G06T7/0012 , G06T7/12 , G06T2207/10056 , G06T2207/20016 , G06T2207/20036 , G06T2207/20072 , G06T2207/20076 , G06T2207/20081 , G06T2207/20152 , G06T2207/30024
Abstract: A method of segmenting a digital image of biological tissue includes accessing a ranking model calculated from training data representing shapes of conforming and non-conforming biological unit exemplars. The ranking model may include support vectors defining a hyperplane in a vector space. The method further includes accessing image data representing the digital image, identifying a first shape and a set of second constituent shapes in the digital image, wherein the first shape comprises a union of the set of second constituent shapes, determining a rank of a first data point in the image data corresponding to the first shape and a rank of a second data point in the image data corresponding to the set of second constituent shapes into the vector space, and segmenting the digital image using the first shape or the set of second constituent shapes based on which data point has a greater respective rank.
Abstract translation: 分割生物组织的数字图像的方法包括访问由表示符合和不符合生物单元样本的形状的训练数据计算的排名模型。 排名模型可以包括在向量空间中定义超平面的支持向量。 该方法还包括访问表示数字图像的图像数据，识别数字图像中的第一形状和一组第二组成形状，其中第一形状包括该组第二组成形状的并集，确定第一数据的等级 将对应于该第二构成形状的图像数据中的第一形状的图像数据和第二数据点的等级指向矢量空间，并且使用第一形状或第二成分组合分割数字图像 基于哪个数据点具有更大的相应等级的形状。
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10.发明申请System and Method for Multiplexed Biomarker Quantitation Using Single Cell Segmentation on Sequentially Stained Tissue 有权用于使用单细胞分割进行连续染色组织的多重生物标志物定量的系统和方法公开(公告)号：US20140314299A1
公开(公告)日：2014-10-23
申请号：US13865036
申请日：2013-04-17
Applicant: General Electric Company
Inventor： Alberto Santamaria-Pang , Jens Rittscher , Dirk Padfield , Ali Can , Zhengyu Pang , Musodiq Bello , Fiona Ginty , Christopher Sevinsky , Qing Li , Megan Rothney , Brion Sarachan
IPC: G06K9/00
CPC classification number: G06K9/0014 , G06T7/0012 , G06T2207/10064 , G06T2207/30024
Abstract: Improved systems and methods for the analysis of digital images are provided. More particularly, the present disclosure provides for improved systems and methods for the analysis of digital images of biological tissue samples. Exemplary embodiments provide for: i) segmenting, ii) grouping, and iii) quantifying molecular protein profiles of individual cells in terms of sub cellular compartments (nuclei, membrane, and cytoplasm). The systems and methods of the present disclosure advantageously perform tissue segmentation at the sub-cellular level to facilitate analyzing, grouping and quantifying protein expression profiles of tissue in tissue sections globally and/or locally. Performing local-global tissue analysis and protein quantification advantageously enables correlation of spatial and molecular configuration of cells with molecular information of different types of cancer.
Abstract translation: 提供了改进的数字图像分析系统和方法。 更具体地，本公开提供了用于分析生物组织样本的数字图像的改进的系统和方法。 示例性实施方案提供：i）分段，ii）分组，和iii）根据亚细胞区室（细胞核，膜和细胞质）量化各细胞的分子蛋白质谱。 本公开的系统和方法有利地在亚细胞水平进行组织分割，以便于全局和/或局部地分析，分组和定量组织部位中组织的蛋白质表达谱。 进行局部全局组织分析和蛋白质定量有利于使细胞的空间和分子构型与不同类型癌症的分子信息的相关性。
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