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1.发明授权公开(公告)号：US08369600B2
公开(公告)日：2013-02-05
申请号：US12055038
申请日：2008-03-25
CPC分类号： G01N1/312 , G01N2001/368 , G01N2800/60
摘要： The present techniques provide systems and methods for registering images of tissue spots on a tissue microarray (TMA). In studies involving multiple biomarkers being studied on the same TMA, the TMA slide is removed from the microscope, stained, and then imaged, often multiple times. The present techniques relate to validation of the registration of the acquired images of the same TMA. An automatic approach to register the images and detect registration failures as provided herein may enhance the rapid analysis of the tissues. Artifacts such as tissue folding and tissue loss are also determined automatically.
摘要翻译： 本技术提供了用于在组织微阵列（TMA）上记录组织斑点的图像的系统和方法。 在涉及在相同TMA上研究的多种生物标志物的研究中，将TMA载玻片从显微镜中除去，染色，然后成像，通常多次。 本技术涉及对相同TMA的所获取的图像的注册的验证。 如本文所提供的注册图像和检测登记失败的自动方法可以增强组织的快速分析。 人工制品如组织折叠和组织损失也自动确定。
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公开(公告)号：US20090247416A1
公开(公告)日：2009-10-01
申请号：US12055121
申请日：2008-03-25
CPC分类号： G01N21/6452 , G06T7/30 , G06T2207/30072
摘要： The present techniques include methods and systems for finding correspondences between tissue spots in tissue microarray serial sections belonging to the same recipient block. The present techniques may also be used to relate individual tissue cores to clinical information. Using either a whole slide image or the relative x-y coordinates of the tissue spots on the slide, individual tissue spots in different tissue microarrays may be linked to one another and their clinical information.
摘要翻译： 本技术包括用于在属于相同受体块的组织微阵列序列区段中发现组织斑点之间的对应关系的方法和系统。 本技术还可以用于将个体组织核心与临床信息相关联。 使用整个幻灯片图像或幻灯片上组织斑点的相对x-y坐标，不同组织微阵列中的各个组织斑点可以彼此连接并且其临床信息。
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3.发明申请公开(公告)号：US20090245610A1
公开(公告)日：2009-10-01
申请号：US12055038
申请日：2008-03-25
IPC分类号： G01N33/52
CPC分类号： G01N1/312 , G01N2001/368 , G01N2800/60
摘要： The present techniques provide systems and methods for registering images of tissue spots on a tissue microarray (TMA). In studies involving multiple biomarkers being studied on the same TMA, the TMA slide is removed from the microscope, stained, and then imaged, often multiple times. The present techniques relate to validation of the registration of the acquired images of the same TMA. An automatic approach to register the images and detect registration failures as provided herein may enhance the rapid analysis of the tissues. Artifacts such as tissue folding and tissue loss are also determined automatically.
摘要翻译： 本技术提供了用于在组织微阵列（TMA）上记录组织斑点的图像的系统和方法。 在涉及在相同TMA上研究的多种生物标志物的研究中，将TMA载玻片从显微镜中除去，染色，然后成像，通常多次。 本技术涉及对相同TMA的所获取的图像的注册的验证。 如本文所提供的注册图像和检测登记失败的自动方法可以增强组织的快速分析。 人工制品如组织折叠和组织损失也自动确定。
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公开(公告)号：US08880351B2
公开(公告)日：2014-11-04
申请号：US12055121
申请日：2008-03-25
CPC分类号： G01N21/6452 , G06T7/30 , G06T2207/30072
摘要： The present techniques include methods and systems for finding correspondences between tissue spots in tissue microarray serial sections belonging to the same recipient block. The present techniques may also be used to relate individual tissue cores to clinical information. Using either a whole slide image or the relative x-y coordinates of the tissue spots on the slide, individual tissue spots in different tissue microarrays may be linked to one another and their clinical information.
摘要翻译： 本技术包括用于在属于相同受体块的组织微阵列序列区段中发现组织斑点之间的对应关系的方法和系统。 本技术还可以用于将个体组织核心与临床信息相关联。 使用整个幻灯片图像或幻灯片上组织斑点的相对x-y坐标，不同组织微阵列中的各个组织斑点可以彼此连接并且其临床信息。
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公开(公告)号：US20090245611A1
公开(公告)日：2009-10-01
申请号：US12056078
申请日：2008-03-26
申请人： Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
发明人： Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
IPC分类号： G06K9/00
CPC分类号： G06K9/0014 , G01N21/6458
摘要： Techniques for removing image autoflourescence from fluorescently stained biological images are provided herein. The techniques utilize non-negative matrix factorization that may constrain mixing coefficients to be non-negative. The probability of convergence to local minima is reduced by using smoothness constraints. The non-negative matrix factorization algorithm provides the advantage of removing both dark current and autofluorescence.
摘要翻译： 本文提供了从荧光染色的生物图像中去除图像自动曝光的技术。 这些技术利用可以将混合系数限制为非负的非负矩阵分解。 通过使用平滑度约束来减少收敛到局部最小值的概率。 非负矩阵分解算法提供了去除暗电流和自发荧光的优点。
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公开(公告)号：US20090245598A1
公开(公告)日：2009-10-01
申请号：US12056068
申请日：2008-03-26
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T2207/30072
摘要： The present techniques provide fully automated methods for quantifying the location, strength and percent of expressed target molecules or other biological markers in immunohistochemically stained biological samples. The samples may be automatically segmented, for example into subcellular compartments, from images of compartmental markers. Then, the distribution of a target molecule on each of these compartments is calculated that includes the percentage and strength of expression. This is different than existing intensity or ratio based methods where abundant low expression levels are indistinguishable from scarce high expression levels.
摘要翻译： 本技术提供了完全自动化的方法，用于定量免疫组织化学染色的生物样品中表达的靶分子或其他生物标志物的位置，强度和百分比。 样品可以从分隔标记的图像中自动分割，例如分成亚细胞室。 然后，计算这些隔室中的每一个上的靶分子的分布，其包括表达的百分比和强度。 这与现有的强度或基于比例的方法不同，其中丰富的低表达水平与稀缺的高表达水平无法区分。
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公开(公告)号：US08189884B2
公开(公告)日：2012-05-29
申请号：US12056068
申请日：2008-03-26
CPC分类号： G06T7/0012 , G06T2207/30072
摘要： The present techniques provide fully automated methods for quantifying the location, strength and percent of expressed target molecules or other biological markers in immunohistochemically stained biological samples. The samples may be automatically segmented, for example into subcellular compartments, from images of compartmental markers. Then, the distribution of a target molecule on each of these compartments is calculated that includes the percentage and strength of expression. This is different than existing intensity or ratio based methods where abundant low expression levels are indistinguishable from scarce high expression levels.
摘要翻译： 本技术提供了完全自动化的方法，用于定量免疫组织化学染色的生物样品中表达的靶分子或其他生物标志物的位置，强度和百分比。 样品可以从分隔标记的图像中自动分割，例如分成亚细胞室。 然后，计算这些隔室中的每一个上的靶分子的分布，其包括表达的百分比和强度。 这与现有的强度或基于比例的方法不同，其中丰富的低表达水平与稀缺的高表达水平无法区分。
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公开(公告)号：US08135187B2
公开(公告)日：2012-03-13
申请号：US12056078
申请日：2008-03-26
申请人： Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
发明人： Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
CPC分类号： G06K9/0014 , G01N21/6458
摘要： Techniques for removing image autoflourescence from fluorescently stained biological images are provided herein. The techniques utilize non-negative matrix factorization that may constrain mixing coefficients to be non-negative. The probability of convergence to local minima is reduced by using smoothness constraints. The non-negative matrix factorization algorithm provides the advantage of removing both dark current and autofluorescence.
摘要翻译： 本文提供了从荧光染色的生物图像中去除图像自动曝光的技术。 这些技术利用可以将混合系数限制为非负的非负矩阵分解。 通过使用平滑度约束来减少收敛到局部最小值的概率。 非负矩阵分解算法提供了去除暗电流和自发荧光的优点。
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公开(公告)号：US08036462B2
公开(公告)日：2011-10-11
申请号：US11680063
申请日：2007-02-28
IPC分类号： G06K9/34
CPC分类号： G06T7/0012 , G06K9/0061 , G06T7/41 , G06T2207/10116 , G06T2207/30068
摘要： Methods and systems for segmenting images, wherein the image pixels are categorized into a plurality of subsets using one or more indexes, then a log-likelihood function of one or more of the indexes is determined, and one or more maps are generated based on the determination of the log-likelihood function of one or more of the indexes.
摘要翻译： 用于分割图像的方法和系统，其中使用一个或多个索引将图像像素分类为多个子集，然后确定一个或多个索引的对数似然函数，并且基于 确定一个或多个索引的对数似然函数。
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公开(公告)号：US20080031521A1
公开(公告)日：2008-02-07
申请号：US11680063
申请日：2007-02-28
IPC分类号： G06K9/34
CPC分类号： G06T7/0012 , G06K9/0061 , G06T7/41 , G06T2207/10116 , G06T2207/30068
摘要： Methods and systems for segmenting images, wherein the image pixels are categorized into a plurality of subsets using one or more indexes, then a log-likelihood function of one or more of the indexes is determined, and one or more maps are generated based on the determination of the log-likelihood function of one or more of the indexes.
摘要翻译： 用于分割图像的方法和系统，其中使用一个或多个索引将图像像素分类为多个子集，然后确定一个或多个索引的对数似然函数，并且基于 确定一个或多个索引的对数似然函数。
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