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1.发明授权Biopolymeric array scanners capable of automatic scale factor selection for a plurality of different dyes, and methods for making and using the same 失效能够对多种不同染料进行自动比例因子选择的生物聚合物阵列扫描器及其制造和使用方法公开(公告)号：US07331511B2
公开(公告)日：2008-02-19
申请号：US10328109
申请日：2002-12-23
申请人： John F. Corson , Scott D. Connell , Srinka Ghosh
发明人： John F. Corson , Scott D. Connell , Srinka Ghosh
IPC分类号： G06F17/00
CPC分类号： G01N21/6452 , G01N21/6428 , G01N2201/1241
摘要： Biopolymeric array scanners that are capable of automatically selecting a dye specific scale factor to employ for a plurality of different dyes, as wells as methods for making and using the same, are provided. In many embodiments, the actual dye specific scale factor automatically selected by the scanner is one that is equal to a preset “master” scale factor, so that the scanner reads any supported dye using the same constant scale factor. The dye specific scale factor selection is typically made by reference to a collection of nominal scale factors for each member of the plurality of dyes. In using the subject scanners, a user simply inputs the one or more dyes being used in a given array assay, and the scanner automatically reads the array using an automatically chosen dye specific scale factor for the selected dyes. Also provided are methods of obtaining collections of nominal scale factors and computer readable mediums comprising the same. The subject invention finds use in a variety of different applications, including both genomics and proteomics applications.
摘要翻译： 提供了能够自动选择染料比例因子以用于多种不同染料的生物聚合物阵列扫描仪，作为制备和使用它们的方法的孔。 在许多实施例中，由扫描仪自动选择的实际染料特异性比例因子等于预设的“主”比例因子，使得扫描器使用相同的恒定比例因子读取任何支持的染料。 染料比例因子选择通常参考多个染料中每个成员的标称比例因子的集合来进行。 在使用主题扫描仪时，用户只需输入在给定阵列测定中使用的一种或多种染料，并且扫描仪使用所选染料的自动选择的染料比例因子自动读取阵列。 还提供了获得标称比例因子的集合的方法以及包括其的计算机可读介质。 本发明可用于各种不同的应用，包括基因组学和蛋白质组学应用。
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公开(公告)号：US20080161206A1
公开(公告)日：2008-07-03
申请号：US12005542
申请日：2007-12-26
申请人： John F. Corson , Scott D. Connell , Srinka Ghosh
发明人： John F. Corson , Scott D. Connell , Srinka Ghosh
CPC分类号： G01N21/6452 , G01N21/6428 , G01N2201/1241
摘要： Biopolymeric array scanners that are capable of automatically selecting a dye specific scale factor to employ for a plurality of different dyes, as wells as methods for making and using the same, are provided. In many embodiments, the actual dye specific scale factor automatically selected by the scanner is one that is equal to a preset “master” scale factor, so that the scanner reads any supported dye using the same constant scale factor. The dye specific scale factor selection is typically made by reference to a collection of nominal scale factors for each member of the plurality of dyes. In using the subject scanners, a user simply inputs the one or more dyes being used in a given array assay, and the scanner automatically reads the array using an automatically chosen dye specific scale factor for the selected dyes. Also provided are methods of obtaining collections of nominal scale factors and computer readable mediums comprising the same. The subject invention finds use in a variety of different applications, including both genomics and proteomics applications.
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3.发明授权公开(公告)号：US07663529B2
公开(公告)日：2010-02-16
申请号：US11889637
申请日：2007-08-15
IPC分类号： G01S13/00
CPC分类号： G01S13/9011
摘要： Provided are two-dimensional autofocus methods in a synthetic aperture radar (SAR) system which include: (1) two-dimensional pulse pair product algorithm including shear PGA, eigenvector phase history (“EPH”), shear PGA/EPH); (2) two-dimensional optimization algorithms including parametric one-dimensional estimate/two-dimensional correction, parametric two dimensional estimate/two-dimensional correction, unconstrained two-dimensional nonparametric and constrained two-dimensional nonparametric methods; (3) a two-dimensional geometry filter algorithm; (4) a two-dimensional prominent point processing algorithm; (5) a one-dimensional phase estimate of higher order two dimensional phase errors; and, (6) a fast SHARP parametric autofocus algorithm.
摘要翻译： 提供了一种合成孔径雷达（SAR）系统中的二维自动对焦方法，包括：（1）包括剪切PGA，特征向量相位历史（“EPH”），剪切PGA / EPH的二维脉冲对产品算法; （2）二维优化算法，包括参数一维估计/二维校正，参数二维估计/二维校正，无约束二维非参数和约束二维非参数方法; （3）二维几何滤波算法; （4）二维突出点处理算法; （5）高阶二维相位误差的一维相位估计; 和（6）快速SHARP参数自动对焦算法。
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公开(公告)号：US20110133983A1
公开(公告)日：2011-06-09
申请号：US12926602
申请日：2010-11-29
IPC分类号： G01S13/90
CPC分类号： G01S13/9011
摘要： Provided are two-dimensional autofocus methods in a synthetic aperture radar (SAR) system which include: (1) two-dimensional pulse pair product algorithm including shear PGA, eigenvector phase history (“EPH”), shear PGA/EPH); (2) two-dimensional optimization algorithms including parametric one-dimensional estimate/two-dimensional correction, parametric two dimensional estimate/two-dimensional correction, unconstrained two-dimensional nonparametric and constrained two-dimensional nonparametric methods; (3) a two-dimensional geometry filter algorithm; (4) a two-dimensional prominent point processing algorithm; (5) a one-dimensional phase estimate of higher order two dimensional phase errors; and, (6) a fast SHARP parametric autofocus algorithm.
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5.发明申请公开(公告)号：US20100149024A1
公开(公告)日：2010-06-17
申请号：US12656689
申请日：2010-02-12
IPC分类号： G01S13/90
CPC分类号： G01S13/9011
摘要： Provided are two-dimensional autofocus methods in a synthetic aperture radar (SAR) system which include: (1) two-dimensional pulse pair product algorithm including shear PGA, eigenvector phase history (“EPH”), shear PGA/EPH); (2) two-dimensional optimization algorithms including parametric one-dimensional estimate/two-dimensional correction, parametric two dimensional estimate/two-dimensional correction, unconstrained two-dimensional nonparametric and constrained two-dimensional nonparametric methods; (3) a two-dimensional geometry filter algorithm; (4) a two-dimensional prominent point processing algorithm; (5) a one-dimensional phase estimate of higher order two dimensional phase errors; and, (6) a fast SHARP parametric autofocus algorithm.
摘要翻译： 提供了一种合成孔径雷达（SAR）系统中的二维自动对焦方法，包括：（1）包括剪切PGA，特征向量相位历史（“EPH”），剪切PGA / EPH的二维脉冲对产品算法; （2）二维优化算法，包括参数一维估计/二维校正，参数二维估计/二维校正，无约束二维非参数和约束二维非参数方法; （3）二维几何滤波算法; （4）二维突出点处理算法; （5）高阶二维相位误差的一维相位估计; 和（6）快速SHARP参数自动对焦算法。
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公开(公告)号：US06993172B2
公开(公告)日：2006-01-31
申请号：US09895756
申请日：2001-06-29
申请人： Scott D. Connell , Herbert F. Cattell , Glenda C. Delenstarr , Nicholas M Sampas , Andreas N. Dorsel
发明人： Scott D. Connell , Herbert F. Cattell , Glenda C. Delenstarr , Nicholas M Sampas , Andreas N. Dorsel
IPC分类号： G06K9/00
CPC分类号： G01N21/253
摘要： A method and system for employing pixel-based, signal-intensity data contained within areas of a scanned image of a molecular array corresponding to features and feature backgrounds in order to determine whether or not the features or feature backgrounds have non-uniform signal intensities and are thus outlier features and outlier feature backgrounds. A calculated, estimated variance for the signal intensities within a feature or feature background is compared to a maximum allowable variance calculated for the feature or feature background based on a signal intensity variance model. When the experimental variance is less than or equal to the maximum allowable variance, the feature or feature background is considered to have acceptable signal-intensity uniformity. Otherwise, the feature or feature background is flagged as an outlier feature or outlier feature background.
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7.发明授权公开(公告)号：US08009079B2
公开(公告)日：2011-08-30
申请号：US12926602
申请日：2010-11-29
IPC分类号： G01S13/00
CPC分类号： G01S13/9011
摘要： Provided are two-dimensional autofocus methods in a synthetic aperture radar (SAR) system which include: (1) two-dimensional pulse pair product algorithm including shear PGA, eigenvector phase history (“EPH”), shear PGA/EPH); (2) two-dimensional optimization algorithms including parametric one-dimensional estimate/two-dimensional correction, parametric two dimensional estimate/two-dimensional correction, unconstrained two-dimensional nonparametric and constrained two-dimensional nonparametric methods; (3) a two-dimensional geometry filter algorithm; (4) a two-dimensional prominent point processing algorithm; (5) a one-dimensional phase estimate of higher order two dimensional phase errors; and, (6) a fast SHARP parametric autofocus algorithm.
摘要翻译： 提供了一种合成孔径雷达（SAR）系统中的二维自动对焦方法，包括：（1）包括剪切PGA，特征向量相位历史（“EPH”），剪切PGA / EPH的二维脉冲对产品算法; （2）二维优化算法，包括参数一维估计/二维校正，参数二维估计/二维校正，无约束二维非参数和约束二维非参数方法; （3）二维几何滤波算法; （4）二维突出点处理算法; （5）高阶二维相位误差的一维相位估计; 和（6）快速SHARP参数自动对焦算法。
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公开(公告)号：US07843377B2
公开(公告)日：2010-11-30
申请号：US12656689
申请日：2010-02-12
IPC分类号： G01S13/00
CPC分类号： G01S13/9011
摘要： Provided are two-dimensional autofocus methods in a synthetic aperture radar (SAR) system which include: (1) two-dimensional pulse pair product algorithm including shear PGA, eigenvector phase history (“EPH”), shear PGA/EPH); (2) two-dimensional optimization algorithms including parametric one-dimensional estimate/two-dimensional correction, parametric two dimensional estimate/two-dimensional correction, unconstrained two-dimensional nonparametric and constrained two-dimensional nonparametric methods; (3) a two-dimensional geometry filter algorithm; (4) a two-dimensional prominent point processing algorithm; (5) a one-dimensional phase estimate of higher order two dimensional phase errors; and, (6) a fast SHARP parametric autofocus algorithm.
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公开(公告)号：US07006927B2
公开(公告)日：2006-02-28
申请号：US10086839
申请日：2002-02-28
申请人： Zohar Yakhini , Cynthia Y. Enderwick , Glenda C. Delenstarr , Paul K. Wolber , Nicholas M. Sampas , Herbert F. Cattell , Scott D. Connell
发明人： Zohar Yakhini , Cynthia Y. Enderwick , Glenda C. Delenstarr , Paul K. Wolber , Nicholas M. Sampas , Herbert F. Cattell , Scott D. Connell
IPC分类号： G06F11/32
CPC分类号： G06T7/73 , G06T2207/30072
摘要： A method and system for extracting data signals from a scanned image resulting from optical, radiometric, or other types of analysis of a molecular array. The positions of corner features are first located. Then, an initial feature coordinate grid is determined from the positions of the corner features. A refined feature coordinate grid is then calculated based on the positions of strong features, and is used to identify the positions of weak features and the positions of the local background regions surrounding all features. Finally, signal intensity values are extracted from the features and their respective local background regions in the scanned image, and background-subtracted signal intensity values, background-subtracted and normalized signal intensity ratios, and variability information and confidence intervals are determined based on the extracted values.
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