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1.发明申请公开(公告)号：US20190080146A1
公开(公告)日：2019-03-14
申请号：US15703835
申请日：2017-09-13
Applicant: General Electric Company
Inventor： Alberto Santamaria-Pang , Qing Li , Yunxia Sui , Dmitry Vladimirovich Dylov , Christopher James Sevinsky , Michael E. Marino , Michael J. Gerdes , Daniel Eugene Meyer , Fiona Ginty , Anup Sood
CPC classification number: G06K9/00147 , G06T7/0012 , G06T7/33 , G06T2207/10024 , G06T2207/10056 , G06T2207/20104 , G06T2207/30024
Abstract: The subject matter of the present disclosure generally relates to techniques for image analysis. In certain embodiments, various morphological or intensity-based features as well as different thresholding approaches may be used to segment the subpopulation of interest and classify object in the images.
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2.发明申请公开(公告)号：US20180121760A1
公开(公告)日：2018-05-03
申请号：US15796379
申请日：2017-10-27
Applicant: General Electric Company
Inventor： Alberto Santamaria-Pang , Daniel Eugene Meyer , Michael Ernest Marino , Qing Li , Dmitry V. Dylov , Aritra Chowdhury
CPC classification number: G06K9/6256 , G06K9/44 , G06K9/6267 , G06K9/6274 , G06K2209/05 , G06N3/04 , G06N3/0454 , G06N3/08 , G06N3/084 , G06T7/0012 , G06T7/11 , G06T7/155 , G06T2200/04 , G06T2207/10056 , G06T2207/10064 , G06T2207/30016 , G06T2207/30101 , G06T2207/30172 , G09B23/30 , G09B23/303 , G16H50/20 , G16H50/50
Abstract: The present approach relates to the use of trained artificial neural networks, such as convolutional neural networks, to classify vascular structures, such as using a hierarchical classification scheme. In certain approaches, the artificial neural network is trained using training data that is all or partly derived from synthetic vascular representations.
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公开(公告)号：US20160220129A1
公开(公告)日：2016-08-04
申请号：US14614026
申请日：2015-02-04
Applicant: General Electric Company
Inventor： Victor Petrovich Ostroverkhov , Alberto Santamaria-Pang , Dmitry V. Dylov , Ali Can , Siavash Yazdanfar
CPC classification number: A61B5/0261 , A61B5/02007 , A61B5/6815 , A61B2562/0238 , A61B2576/00
Abstract: A method in one embodiment includes acquiring optical image information with a detection unit configured to be operably coupled to a patient. The optical image information corresponds to microcirculation of the patient. The method also includes generating a microcirculation map of microvasculature of the patient using the optical image information. Further, the method includes generating a quantitative microcirculation index based on the microcirculation map, the quantitative microcirculation index corresponding to a condition of the patient.
Abstract translation: 一个实施例中的方法包括采用被配置为可操作地耦合到患者的检测单元获取光学图像信息。 光学图像信息对应于患者的微循环。 该方法还包括使用光学图像信息产生患者的微血管微循环图。 此外，该方法包括基于微循环图生成与患者状况对应的定量微循环指标的定量微循环指标。
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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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5.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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Patent Agency Ranking
公开(公告)号：US11971329B2
公开(公告)日：2024-04-30
申请号：US17538717
申请日：2021-11-30
Applicant: General Electric Company
Inventor： Brandon S. Good , Bijan Chitsaz , Guanghua Wang , Bernard P. Bewlay , Gyeong Woo Cheon , Alberto Santamaria-Pang
CPC classification number: G01M3/38 , F02C7/00 , G01J5/0003 , G06T7/0002 , G06T7/90 , G08B21/182 , H04N23/90 , F05D2260/80 , G01J2005/0077 , G06T2207/10048 , G06T2207/20084
Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to autonomously detect thermal anomalies. Disclosed examples include an example apparatus to detect engine anomalies comprising: at least one memory; instructions in the apparatus; and processor circuitry to execute the instructions to: control a plurality of infrared cameras to capture a baseline image set, the baseline image set including at least two thermal images; generate emissivity data based on the baseline image set; provide the baseline image set and the emissivity data to an artificial intelligence model, the artificial intelligence model to generate a reconstructed image set; determine a difference between the baseline image set and the reconstructed image set; and in response to the difference exceeding a threshold, generate an alert indicating detection of an engine anomaly.
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7.发明授权公开(公告)号：US10423820B2
公开(公告)日：2019-09-24
申请号：US15703835
申请日：2017-09-13
Applicant: General Electric Company
Inventor： Alberto Santamaria-Pang , Qing Li , Yunxia Sui , Dmitry Vladimirovich Dylov , Christopher James Sevinsky , Michael E. Marino , Michael J. Gerdes , Daniel Eugene Meyer , Fiona Ginty , Anup Sood
Abstract: The subject matter of the present disclosure generally relates to techniques for image analysis. In certain embodiments, various morphological or intensity-based features as well as different thresholding approaches may be used to segment the subpopulation of interest and classify object in the images.
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公开(公告)号：US10070796B2
公开(公告)日：2018-09-11
申请号：US14614026
申请日：2015-02-04
Applicant: General Electric Company
Inventor： Victor Petrovich Ostroverkhov , Alberto Santamaria-Pang , Dmitry V. Dylov , Ali Can , Siavash Yazdanfar
CPC classification number: A61B5/0261 , A61B5/02007 , A61B5/6815 , A61B2562/0238 , A61B2576/00
Abstract: A method in one embodiment includes acquiring optical image information with a detection unit configured to be operably coupled to a patient. The optical image information corresponds to microcirculation of the patient. The method also includes generating a microcirculation map of microvasculature of the patient using the optical image information. Further, the method includes generating a quantitative microcirculation index based on the microcirculation map, the quantitative microcirculation index corresponding to a condition of the patient.
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公开(公告)号：US09778263B2
公开(公告)日：2017-10-03
申请号：US14079347
申请日：2013-11-13
Applicant: General Electric Company
Inventor： Srabani Bhaumik , Michael John Gerdes , Zhengyu Pang , Fiona Ginty , Christopher James Sevinsky , Qing Li , Alberto Santamaria-Pang , Yunxia Sui , Keyur Hemantkumar Desai
IPC: G01N33/574 , G01N33/569 , G01N33/543 , G06T7/00 , G06K9/00 , G01N1/30
CPC classification number: G01N33/57492 , G01N1/30 , G01N33/54393 , G01N33/56972 , G01N33/56977 , G06K9/00147 , G06T7/0012 , G06T2207/10024 , G06T2207/30024
Abstract: The present disclosure relates to characterization of biological samples. By way of example, a biological sample may be contacted with a plurality of probes specific for targets in the sample, such as probes for immune markers and segmenting probes. Acquired image data of the sample may be used to segment the images into epithelial and stromal regions to characterize individual cells in the sample based on the binding of the probes. Further, the biological sample may be characterized by a distribution, location, and type of a plurality of the characterized cells.
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公开(公告)号：US20150133321A1
公开(公告)日：2015-05-14
申请号：US14079347
申请日：2013-11-13
Applicant: General Electric Company
Inventor： Srabani Bhaumik , Michael John Gerdes , Zhengyu Pang , Fiona Ginty , Christopher James Sevinsky, JR. , Qing Li , Alberto Santamaria-Pang , Yunxia Sui , Keyur Hemantkumar Desai
IPC: G01N33/574
CPC classification number: G01N33/57492 , G01N1/30 , G01N33/54393 , G01N33/56972 , G01N33/56977 , G06K9/00147 , G06T7/0012 , G06T2207/10024 , G06T2207/30024
Abstract: The present disclosure relates to characterization of biological samples. By way of example, a biological sample may be contacted with a plurality of probes specific for targets in the sample, such as probes for immune markers and segmenting probes. Acquired image data of the sample may be used to segment the images into epithelial and stromal regions to characterize individual cells in the sample based on the binding of the probes. Further, the biological sample may be characterized by a distribution, location, and type of a plurality of the characterized cells.
Abstract translation: 本公开涉及生物样品的表征。 举例来说，可以将生物样品与样品中靶标特异性的多种探针接触，例如用于免疫标记和分割探针的探针。 可以使用样本的获取图像数据将图像分割成上皮和基质区域，以基于探针的结合来表征样品中的各个细胞。 此外，生物样品可以由多个表征的细胞的分布，位置和类型来表征。
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