公开(公告)号：US20130124104A1

公开(公告)日：2013-05-16

申请号：US13737236

申请日：2013-01-09

申请人： Gordana Ivosev

发明人： Gordana Ivosev

IPC分类号： H01J49/00

CPC分类号： H01J49/0036 ,  H01J49/4265

摘要： Systems and methods are used to predict intensities for points not measured or not measured with a high degree of confidence of a peak using a peak predictor. A set of data is selected from the plurality of intensity measurements that includes a peak. Confidence values are assigned to each data point in the set of data producing a plurality of confidence value weighted data points. A peak predictor is selected. The peak predictor is applied to the plurality of confidence value weighted data points of the peak that have confidence values greater than a first threshold level using the prediction module, producing predicted intensities for data points of the peak not measured and/or measured data points of the peak that have confidence values less than or equal to a second threshold level. The confidence values can include system confidence values, predictor confidence values, or any combination of the two.

摘要翻译： 系统和方法用于使用峰值预测器以峰值的高置信度来预测未测量或未测量的点的强度。 从包括峰值的多个强度测量值中选择一组数据。 将置信度值分配给产生多个置信度值加权数据点的数据集合中的每个数据点。 选择峰值预测器。 使用预测模块将峰值预测器应用于具有大于第一阈值水平的置信度值的峰值的多个置信值加权数据点，产生未测量的峰值和/或测量数据点的数据点的预测强度 具有小于或等于第二阈值水平的置信度值的峰值。 置信度值可以包括系统置信度值，预测器置信度值或两者的任何组合。

公开(公告)号：US07638764B2

公开(公告)日：2009-12-29

申请号：US12023873

申请日：2008-01-31

申请人： Gordana Ivosev

发明人： Gordana Ivosev

IPC分类号： H01J49/26 ,  H01J49/00

CPC分类号： H01J49/0036

摘要： Systems and methods for reducing background noise in a mass spectrum. The method includes the following steps of: (a) obtaining an original mass spectrum; (b) determining a noise mass spectrum corresponding to background noise in the original mass spectrum; and (c) determining a corrected mass spectrum by subtracting the noise mass spectrum from the original mass spectrum. Step (b) of the method may include the steps of: A) effecting a transformation of the original mass spectrum into the frequency domain to obtain an original frequency spectrum; B) identifying at least one dominant frequency in the original frequency spectrum; C) generating a noise frequency spectrum by selectively filtering for said dominant frequencies; and D) determining the noise mass spectrum by effecting a transformation of the noise frequency spectrum into the mass domain. Preferably for each correlated pair of original and noise intensity data points, the minimum value is determined and the noise mass spectrum is modified by making the noise intensity data point equal to the minimum value.

摘要翻译： 降低质谱背景噪声的系统和方法。 该方法包括以下步骤：（a）获得原始质谱; （b）确定与原始质谱中背景噪声相对应的噪声质谱; 和（c）通过从原始质谱中减去噪声质谱来确定校正的质谱。 该方法的步骤（b）可以包括以下步骤：A）将原始质谱变换成频域以获得原始频谱; B）识别原始频谱中的至少一个主频; C）通过选择性地滤波所述主频率来产生噪声频谱; 和D）通过将噪声频谱变换成质量域来确定噪声质谱。 优选地，对于每个相关的原始和噪声强度数据点对，通过使噪声强度数据点等于最小值来确定最小值并修改噪声质谱。

公开(公告)号：US08148678B2

公开(公告)日：2012-04-03

申请号：US12626737

申请日：2009-11-27

申请人： Gordana Ivosev

发明人： Gordana Ivosev

IPC分类号： H01J49/26 ,  H01J49/00

CPC分类号： H01J49/0036

摘要： Systems and methods for reducing background noise in a mass spectrum. The method includes the following steps of: (a) obtaining an original mass spectrum; (b) determining a noise mass spectrum corresponding to background noise in the original mass spectrum; and (c) determining a corrected mass spectrum by subtracting the noise mass spectrum from the original mass spectrum. Step (b) of the method may include the steps of: A) effecting a transformation of the original mass spectrum into the frequency domain to obtain an original frequency spectrum; B) identifying at least one dominant frequency in the original frequency spectrum; C) generating a noise frequency spectrum by selectively filtering for said dominant frequencies; and D) determining the noise mass spectrum by effecting a transformation of the noise frequency spectrum into the mass domain. Preferably for each correlated pair of original and noise intensity data points, the minimum value is determined and the noise mass spectrum is modified by making the noise intensity data point equal to the minimum value.

摘要翻译： 降低质谱背景噪声的系统和方法。 该方法包括以下步骤：（a）获得原始质谱; （b）确定与原始质谱中背景噪声相对应的噪声质谱; 和（c）通过从原始质谱中减去噪声质谱来确定校正的质谱。 该方法的步骤（b）可以包括以下步骤：A）将原始质谱变换成频域以获得原始频谱; B）识别原始频谱中的至少一个主频; C）通过选择性地滤波所述主频率来产生噪声频谱; 和D）通过将噪声频谱变换成质量域来确定噪声质谱。 优选地，对于每个相关的原始和噪声强度数据点对，通过使噪声强度数据点等于最小值来确定最小值并修改噪声质谱。

公开(公告)号：US20100072356A1

公开(公告)日：2010-03-25

申请号：US12626737

申请日：2009-11-27

申请人： Gordana Ivosev

发明人： Gordana Ivosev

IPC分类号： G01D18/00 ,  G06F19/00 ,  H01J49/26

CPC分类号： H01J49/0036

摘要： Systems and methods for reducing background noise in a mass spectrum. The method includes the following steps of: (a) obtaining an original mass spectrum; (b) determining a noise mass spectrum corresponding to background noise in the original mass spectrum; and (c) determining a corrected mass spectrum by subtracting the noise mass spectrum from the original mass spectrum. Step (b) of the method may include the steps of: A) effecting a transformation of the original mass spectrum into the frequency domain to obtain an original frequency spectrum; B) identifying at least one dominant frequency in the original frequency spectrum; C) generating a noise frequency spectrum by selectively filtering for said dominant frequencies; and D) determining the noise mass spectrum by effecting a transformation of the noise frequency spectrum into the mass domain. Preferably for each correlated pair of original and noise intensity data points, the minimum value is determined and the noise mass spectrum is modified by making the noise intensity data point equal to the minimum value.

摘要翻译： 降低质谱背景噪声的系统和方法。 该方法包括以下步骤：（a）获得原始质谱; （b）确定与原始质谱中背景噪声相对应的噪声质谱; 和（c）通过从原始质谱中减去噪声质谱来确定校正的质谱。 该方法的步骤（b）可以包括以下步骤：A）将原始质谱变换成频域以获得原始频谱; B）识别原始频谱中的至少一个主频; C）通过选择性地滤波所述主频率来产生噪声频谱; 和D）通过将噪声频谱变换成质量域来确定噪声质谱。 优选地，对于每个相关的原始和噪声强度数据点对，通过使噪声强度数据点等于最小值来确定最小值并修改噪声质谱。

公开(公告)号：US20090259438A1

公开(公告)日：2009-10-15

申请号：US12102537

申请日：2008-04-14

申请人： Ronald Bonner ,  Gordana Ivosev ,  Min Yang

发明人： Ronald Bonner ,  Gordana Ivosev ,  Min Yang

IPC分类号： H04B15/00 ,  G06F15/00

CPC分类号： G06K9/0051 ,  G01N21/274

摘要： Relative noise is a single scalar value that is used to predict the maximum value of the expected noise at any point and is calculated from the measured signal and a mathematical noise model. The mathematical noise model is selected or estimated from an observation that includes statistical and/or numerical modeling based on a population of measurement points. An absolute noise for a plurality of points of the measured signal is estimated. An array of values is calculated by dividing each of a plurality of points of the absolute noise by a corresponding expected noise value calculated from the mathematical noise model. The relative noise is calculated by taking a standard deviation of a plurality of points of the array. The relative noise can be used to calculate scaled background signal noise, filter regions, denoise data, detect false positives from features, calculate S/N, and determine a stop condition for acquiring data.

摘要翻译： 相对噪声是单个标量值，用于预测任何点处预期噪声的最大值，并根据测量信号和数学噪声模型计算。 从包括基于测量点总数的统计学和/或数值模拟的观察中选择或估计数学噪声模型。 估计测量信号的多个点的绝对噪声。 通过将绝对噪声的多个点中的每一个除以由数学噪声模型计算的对应的预期噪声值来计算值的数组。 通过取数组的多个点的标准偏差来计算相对噪声。 相对噪声可用于计算缩放背景信号噪声，滤波器区域，去噪数据，检测特征中的误报，计算S / N，并确定采集数据的停止条件。

公开(公告)号：US08530828B2

公开(公告)日：2013-09-10

申请号：US13437837

申请日：2012-04-02

申请人： Gordana Ivosev ,  Ronald Bonner

发明人： Gordana Ivosev ,  Ronald Bonner

IPC分类号： H01J49/26 ,  B01D59/44 ,  H04B15/00 ,  G06F17/00

CPC分类号： H01J49/26 ,  H01J49/0036

摘要： A plurality of scans of a sample are performed, producing a plurality of mass spectra. Neighboring mass spectra of the plurality of mass spectra are combined into a collection of mass spectra based on sample location, time, or mass. A background noise estimate is calculated for the collection of mass spectra. The collection of mass spectra is filtered using the background noise estimate, producing a filtered collection of one or more mass spectra. Quantitative or qualitative analysis is performed using the filtered collection of one or more mass spectra. The background noise estimate is calculated by dividing the collection of mass spectra into two or more windows, for example. For each window of the two or more windows, all spectra within each window are combined, producing a combined spectrum for each of the two or more windows. For each combined spectrum, a background noise is estimated.

摘要翻译： 执行样本的多次扫描，产生多个质谱。 基于样品位置，时间或质量将多个质谱的相邻质谱合并成质谱图。 计算质谱收集的背景噪声估计。 使用背景噪声估计来过滤质谱的收集，产生一个或多个质谱的过滤集合。 使用一个或多个质谱的过滤集合进行定量或定性分析。 例如，通过将质谱图的集合除以两个或多个窗口来计算背景噪声估计。 对于两个或多个窗口的每个窗口，组合每个窗口内的所有光谱，为两个或多个窗口中的每个窗口产生组合光谱。 对于每个组合光谱，估计背景噪声。

公开(公告)号：US08374799B2

公开(公告)日：2013-02-12

申请号：US12705539

申请日：2010-02-12

申请人： Gordana Ivosev

发明人： Gordana Ivosev

IPC分类号： G01N23/00

CPC分类号： H01J49/0036 ,  H01J49/4265

摘要： Systems and methods are used to predict intensities of a saturated peak using a peak predictor. A set of data is selected from the plurality of intensity measurements that includes a saturated peak. Confidence values are assigned to each data point in the set of data producing a plurality of confidence value weighted data points. A peak predictor is selected. The peak predictor is applied to the plurality of confidence value weighted data points of the saturated peak producing predicted intensities for the saturated peak. The confidence values can include system confidence values, predictor confidence values, or a combination of system confidence values and predictor confidence values. The peak predictor can be a theoretical model, a dynamic model, an artificial neural network, or an analytical function representing a best fit of a plurality of probability density functions to a first set of measured data that includes a representative non-saturated peak.

摘要翻译： 系统和方法用于使用峰值预测器预测饱和峰的强度。 从包括饱和峰值的多个强度测量中选择一组数据。 将置信度值分配给产生多个置信度值加权数据点的数据集合中的每个数据点。 选择峰值预测器。 将峰值预测器应用于产生饱和峰值的预测强度的饱和峰值的多个置信度值加权数据点。 置信度值可以包括系统置信度值，预测器置信度值，或系统置信度值和预测值置信度值的组合。 峰值预测器可以是理论模型，动态模型，人造神经网络或表示多个概率密度函数对包括代表性非饱和峰值的第一组测量数据的最佳拟合的分析函数。

公开(公告)号：US08073639B2

公开(公告)日：2011-12-06

申请号：US12200636

申请日：2008-08-28

申请人： Gordana Ivosev ,  Ronald Bonner

发明人： Gordana Ivosev ,  Ronald Bonner

IPC分类号： G06F17/00 ,  G06F17/40

CPC分类号： G06K9/00543 ,  G01N30/72 ,  G01N30/8682 ,  G01N2030/862 ,  H01J49/0036

摘要： A method for identifying a convolved peak is described. A plurality of spectra is obtained. A multivariate analysis technique is used to assign data points from the plurality of spectra to a plurality of groups. A peak is selected from the plurality of spectra. If the peak includes data points assigned to two or more groups of the plurality of groups, the peak is identified as a convolved peak. Principal component analysis is one multivariate analysis technique that is used to assign data points. A number of principal components are selected. A subset principal component space is created. A data point in the subset principal component space is selected. A vector is extended from the origin of the subset principal component space to the data point. One or more data points within a spatial angle around the vector are assigned to a group.

摘要翻译： 描述了用于识别卷积峰的方法。 获得多个光谱。 多变量分析技术用于将数据点从多个频谱分配到多个组。 从多个光谱中选出峰。 如果峰值包括分配给多个组中的两个或更多个组的数据点，则将该峰识别为卷积峰。 主成分分析是一种用于分配数据点的多变量分析技术。 选择了多个主要组件。 创建子集主体组件空间。 选择子集主体组件空间中的数据点。 向量从子集主体组件空间的起点扩展到数据点。 在矢量周围的空间角度内的一个或多个数据点被分配给一个组。

公开(公告)号：US20110202287A1

公开(公告)日：2011-08-18

申请号：US12705539

申请日：2010-02-12

申请人： Gordana Ivosev

发明人： Gordana Ivosev

IPC分类号： G06F19/00 ,  G06F17/18

CPC分类号： H01J49/0036 ,  H01J49/4265

摘要： Systems and methods are used to predict intensities of a saturated peak using a peak predictor. A set of data is selected from the plurality of intensity measurements that includes a saturated peak. Confidence values are assigned to each data point in the set of data producing a plurality of confidence value weighted data points. A peak predictor is selected. The peak predictor is applied to the plurality of confidence value weighted data points of the saturated peak producing predicted intensities for the saturated peak. The confidence values can include system confidence values, predictor confidence values, or a combination of system confidence values and predictor confidence values. The peak predictor can be a theoretical model, a dynamic model, an artificial neural network, or an analytical function representing a best fit of a plurality of probability density functions to a first set of measured data that includes a representative non-saturated peak.

摘要翻译： 系统和方法用于使用峰值预测器预测饱和峰的强度。 从包括饱和峰值的多个强度测量中选择一组数据。 将置信度值分配给产生多个置信度值加权数据点的数据集合中的每个数据点。 选择峰值预测器。 将峰值预测器应用于产生饱和峰值的预测强度的饱和峰值的多个置信度值加权数据点。 置信度值可以包括系统置信度值，预测器置信度值，或系统置信度值和预测值置信度值的组合。 峰值预测器可以是理论模型，动态模型，人造神经网络或表示多个概率密度函数对包括代表性非饱和峰值的第一组测量数据的最佳拟合的分析函数。

公开(公告)号：US20080054175A1

公开(公告)日：2008-03-06

申请号：US11846719

申请日：2007-08-29

申请人： Nic Bloomfield ,  Gordana Ivosev

发明人： Nic Bloomfield ,  Gordana Ivosev

IPC分类号： G06F19/00 ,  H01J49/26

CPC分类号： H01J49/0027

摘要： Systems and methods for calculating ion flux. In one embodiment, a mass spectrometer includes an ion source for emitting a beam of ions from a sample and at least one detector positioned downstream of said ion source. The at least one detector comprises a plurality of detector channels. The mass spectrometer also includes a controller operatively coupled to the plurality of detector channels. The controller is configured to: determine ion abundance data correlated to each detector channel; determine corrected ion abundance data correlated to each detector channel; determine confidence data corresponding to the ion abundance data for each of the detector channels; and determine a confidence weighted abundance estimate of the ion flux correlated to both the ion abundance data and to the confidence data.

摘要翻译： 用于计算离子通量的系统和方法。 在一个实施例中，质谱仪包括用于从样品发射离子束的离子源和位于所述离子源下游的至少一个检测器。 所述至少一个检测器包括多个检测器通道。 质谱仪还包括可操作地耦合到多个检测器通道的控制器。 控制器被配置为：确定与每个检测器通道相关的离子丰度数据; 确定与每个检测器通道相关的校正离子丰度数据; 确定对应于每个检测器通道的离子丰度数据的置信度数据; 并确定与离子丰度数据和置信数据两者相关的离子通量的置信加权丰度估计。