公开(公告)号：US20090317856A1

公开(公告)日：2009-12-24

申请号：US12479600

申请日：2009-06-05

Applicant: Mary-Ann Mycek ,  Malavika Chandra ,  James Scheiman ,  Robert H. Wilson ,  Diane Simeone ,  Barbara McKenna ,  Julianne Purdy

Inventor： Mary-Ann Mycek ,  Malavika Chandra ,  James Scheiman ,  Robert H. Wilson ,  Diane Simeone ,  Barbara McKenna ,  Julianne Purdy

IPC: C12Q1/02 ,  C12M1/34

CPC classification number: G01N33/57438 ,  A61B5/0071 ,  A61B5/0075 ,  A61B5/0084 ,  A61B5/415 ,  A61B5/418 ,  A61B5/7264 ,  A61B5/7267 ,  G01J3/10 ,  G01J3/4406 ,  G01N21/474 ,  G01N21/6408 ,  G01N21/645 ,  G01N21/6486 ,  G01N2021/4742 ,  G01N2021/6484 ,  G01N2201/1293

Abstract: Multimodal optical spectroscopy systems and methods produce a spectroscopic event to obtain spectroscopic response data from biological tissue and compare the response data with preset criteria configured to correlate the measured response data and the most probable attributes of the tissue, thus facilitating classification of the tissue based on those attributes for subsequent biopsy or remedial measures as necessary.

Abstract translation: 多光谱光谱系统和方法产生光谱事件以从生物组织获得光谱响应数据，并将响应数据与配置为将测量的响应数据和组织的最可能属性相关联的预设标准进行比较，从而便于基于 这些属性用于随后的活检或必要的补救措施。

公开(公告)号：US20090287418A1

公开(公告)日：2009-11-19

申请号：US12116673

申请日：2008-05-07

Applicant: Pierre C. Trepagnier ,  Philip D. Henshaw

Inventor： Pierre C. Trepagnier ,  Philip D. Henshaw

IPC: G06F19/00 ,  G01N31/00

CPC classification number: G01J3/28 ,  A62B9/006 ,  G01N21/274 ,  G01N2201/1293 ,  G06F19/703

Abstract: Methods and systems are disclosed for detection of agents such as pathogens or toxic substances and, in particular, to methods and systems for determining the most important background constituents to suppress in a sample, e.g., in a bulk aerosol sample, in order to reduce the probability of false alarms and improve the level of detection of potentially harmful airborne agents.

Abstract translation: 公开了用于检测诸如病原体或有毒物质的试剂的方法和系统，特别是用于确定样品中抑制重要的背景成分的方法和系统，例如在散装气溶胶样品中，以便减少 误报的概率，提高潜在有害空气传播剂的检测水平。

公开(公告)号：US20090121138A1

公开(公告)日：2009-05-14

申请号：US11885739

申请日：2006-03-09

Applicant: Alasdair Iain Thomson

Inventor： Alasdair Iain Thomson

IPC: G01N21/35

CPC classification number: G01N33/28 ,  G01N21/0303 ,  G01N21/3577 ,  G01N21/359 ,  G01N2021/115 ,  G01N2201/129 ,  G01N2201/1293

Abstract: A process for measuring the NIR spectrum of a sample using a demountable NIR transmission cell of pathlength 2.5 mm or less, said process comprising: (a) measuring the etalon fringes that arise when NIR light passes through the NIR cell in the absence of a liquid sample, (b) using this to calculate the pathlength of the NIR cell (c) introducing the sample to be analyzed in to the NIR cell, and (d) measuring the NIR spectrum of the sample.

Abstract translation: 一种使用路径长度为2.5mm或更小的可拆卸NIR传输单元测量样品的近红外光谱的方法，所述方法包括：（a）测量当不存在液体时NIR光通过NIR细胞时产生的标准具条纹 样品，（b）使用它来计算NIR细胞的路径长度（c）将要分析的样品引入NIR细胞，和（d）测量样品的NIR光谱。

公开(公告)号：US20080273199A1

公开(公告)日：2008-11-06

申请号：US12070010

申请日：2008-02-14

Applicant: John Maier ,  Jeffrey Cohen ,  Janice L. Panza ,  Amy J. Drauch

Inventor： John Maier ,  Jeffrey Cohen ,  Janice L. Panza ,  Amy J. Drauch

IPC: G01J3/44

CPC classification number: G01N21/65 ,  G01J3/02 ,  G01J3/0291 ,  G01J3/0294 ,  G01J3/2823 ,  G01J3/44 ,  G01J2003/2826 ,  G01N2021/656 ,  G01N2201/1293 ,  G01N2201/1296

Abstract: A system and method to predict the progression of disease of a test sample. A group of known biological samples is provided. Each known biological sample has an associated known outcome including a non-diseased sample or a diseased sample. A Raman data set is obtained for each known biological sample. Each Raman data set is analyzed to identify a diseased or non-diseased reference Raman data set depending on whether respective biological sample is the non-diseased sample or the diseased sample. A first database is generated where the first database contains reference Raman data sets for all diseased samples. A second database is generated where the second database contains reference Raman data sets for all non-diseased samples. A test Raman data set of a test biological sample is received, where the test biological sample has an unknown disease status. A diagnostic is provided as to whether the test sample is a non-diseased sample or a diseased sample. The diagnostic is obtained by comparing the test Raman data set against the reference Raman data sets in the first and the second databases using a chemometric technique. A prediction of the progression of disease may be then provided.

Abstract translation: 一种预测测试样本疾病进展的系统和方法。 提供了一组已知的生物样品。 每个已知的生物样品具有相关的已知结果，包括非患病样品或患病样品。 获得每个已知生物样品的拉曼数据集。 分析每个拉曼数据集，以根据相应的生物样品是非患病样品还是患病样品来鉴定患病或非患病参考拉曼数据集。 生成第一个数据库，其中第一个数据库包含所有患病样本的参考拉曼数据集。 生成第二数据库，其中第二数据库包含所有非患病样本的参考拉曼数据集。 接受测试生物样品的测试拉曼数据集，其中测试生物样品具有未知的疾病状态。 提供了关于测试样品是否是非患病样品或患病样品的诊断。 通过使用化学计量技术将测试拉曼数据集与第一和第二数据库中的参考拉曼数据集进行比较来获得诊断。 可以提供疾病进展的预测。

公开(公告)号：US07409299B2

公开(公告)日：2008-08-05

申请号：US11407392

申请日：2006-04-18

Applicant: Robert Schweitzer ,  Willem Windig ,  Patrick J. Treado

Inventor： Robert Schweitzer ,  Willem Windig ,  Patrick J. Treado

IPC: G01N31/00

CPC classification number: G01J3/28 ,  G01N21/3577 ,  G01N21/359 ,  G01N33/02 ,  G01N2021/3129 ,  G01N2201/1293 ,  G06F19/703

Abstract: Spectra data collected from a mixture defines an n-dimensional data space (n is the number of data points), and application of PCA techniques yields a subset of m-eigenvectors that effectively describe all variance in that data space. Bach member of a library of known components is examined based by representing each library spectrum as a vector in the m-dimensional space. Target factor testing techniques yield an angle between this vector and the data space. Those library members that have the smallest angles are considered to be potential mixture members and are ranked accordingly. Every combination of the top y library members is considered as a potential solution and a multivariate least-squares solution is calculated using the mixture spectra for each of the potential solutions. A ranking algorithm is then applied and used to select the combination that is most likely the set of pure components in the mixture.

Abstract translation: 从混合物收集的光谱数据定义了n维数据空间（n是数据点的数量），并且PCA技术的应用产生有效描述该数据空间中的所有方差的m个特征向量的子集。 通过将每个库谱表示为m维空间中的向量来检查已知组件的库的Bach成员。 目标因子测试技术在该矢量与数据空间之间产生一个角度。 具有最小角度的那些图书馆成员被认为是潜在的混合成员并被相应排名。 顶级图书馆成员的每个组合都被认为是潜在的解决方案，并且使用每个潜在解决方案的混合谱来计算多变量最小二乘解。 然后应用排序算法并用于选择混合中最可能的纯组分集合的组合。

公开(公告)号：US07329547B2

公开(公告)日：2008-02-12

申请号：US11134442

申请日：2005-05-23

Applicant: Hormoz Azizian

Inventor： Hormoz Azizian

IPC: G01N33/92 ,  G01N21/62

CPC classification number: G01N33/03 ,  G01N21/274 ,  G01N21/3563 ,  G01N21/3577 ,  G01N21/359 ,  G01N2021/3595 ,  G01N2201/1293

Abstract: A method for the rapid analysis of the fatty acid components present in a fat and/or oil-containing material is provided wherein the levels and types of fatty acids present in a sample are determined using Fourier Transform Near Infrared (FT-NIR) spectroscopy. The FT-NIR technique is developed by preparing a calibration matrix based on FT-NIR and Gas Chromatography (GC) analysis of known standards, and subsequently using the calibration matrix to analyze the FT-NIR spectral data obtained from a sample to be tested.

Abstract translation: 提供了用于快速分析存在于脂肪和/或含油材料中的脂肪酸组分的方法，其中使用傅立叶变换近红外（FT-NIR）光谱测定样品中存在的脂肪酸的水平和类型。 FT-NIR技术是通过制备基于已知标准的FT-NIR和气相色谱（GC）分析的校准矩阵开发的，随后使用校准矩阵来分析从待测样品获得的FT-NIR光谱数据。

公开(公告)号：US20080024778A1

公开(公告)日：2008-01-31

申请号：US10576255

申请日：2004-10-15

Applicant: Takayoshi Honda ,  Taichirou Nishiyama ,  Yasuyuki Suga

Inventor： Takayoshi Honda ,  Taichirou Nishiyama ,  Yasuyuki Suga

IPC: G01J3/40 ,  G06F19/00

CPC classification number: G01N21/9508 ,  G01N21/359 ,  G01N21/85 ,  G01N2021/845 ,  G01N2201/1293

Abstract: A detector for detecting a different kind of object among objects being carried with high resolution using a plane spectrometer.

Abstract translation: 一种检测器，用于使用平面光谱仪检测以高分辨率携带的物体中的不同种类的物体。

公开(公告)号：US07127372B2

公开(公告)日：2006-10-24

申请号：US11064290

申请日：2005-02-24

Applicant: Marc Kenneth Boysworth

Inventor： Marc Kenneth Boysworth

IPC: G01N31/00

CPC classification number: G01J3/28 ,  G01N21/31 ,  G01N21/33 ,  G01N21/359 ,  G01N21/65 ,  G01N2021/6417 ,  G01N2201/1293

Abstract: An improved regression-based qualitative analysis algorithm useful when the mixture to be analyzed contains a compound not in the library spectra, a so-called unknown. A regression of a measured spectrum is computed against the library spectra. This regression is referred to as a “master” regression. Estimated mixing coefficients for an estimated spectrum are computed from the regression. Next, a residual error is computed between the estimated spectrum and the measured spectrum. Peaks in the residual error are identified that extend in a direction opposite to that of peaks in the measured spectrum. These peaks are referred to as “negative” peaks. A regression is performed on the peaks. This is referred to as a “retro-regression” to be distinguished from the master regression performed on the measured spectrum. Using information from the retro-regression, corrected mixing coefficients are computed and the process repeats.

Abstract translation: 一种改进的基于回归的定性分析算法，当待分析的混合物含有不在文库谱中的化合物时，这是一种所谓的未知数。 根据文库光谱计算测量光谱的回归。 这个回归被称为“主”回归。 从回归计算估计频谱的估计混合系数。 接下来，在估计的频谱和测量的频谱之间计算残差。 识别残留误差的峰在与测量光谱中的峰的方向相反的方向上延伸。 这些峰被称为“负”峰。 对峰值进行回归。 这被称为“回归”，与在测量光谱上进行的主回归区分开。 使用来自回归回归的信息，计算校正的混合系数并重复该过程。

公开(公告)号：US20060200318A1

公开(公告)日：2006-09-07

申请号：US11218466

申请日：2005-09-06

Applicant: So-ichiro Morishita ,  Hideo Yokota ,  Ryutaro Himeno ,  Taketoshi Mishima

Inventor： So-ichiro Morishita ,  Hideo Yokota ,  Ryutaro Himeno ,  Taketoshi Mishima

IPC: G06F19/00 ,  G01N31/00

CPC classification number: G01N21/6428 ,  G01N2201/1293

Abstract: It is an object of the invention to provide an estimation method of fluorescent dye's concentration from multiple fluorescence, where the accurate estimation of the fluorescent dye's concentration of each fluorescent dye from multiple fluorescence is made possible and the separation of multiple fluorescence which is difficult in the prior art is made possible. In the estimation method of fluorescent dye's concentration from multiple fluorescence where the fluorescent dye's concentration from measured multiple fluorescence, independent component analysis is performed to the spectrum of fluorescent dye where fluorescent dye's concentration is known to derive the intensity of an independent component, regression analysis is performed by using the derived intensity of the independent component as a variable to estimate the fluorescent dye's concentration function of the fluorescent dye where the fluorescent dye's concentration is known, and the concentration of fluorescent dye is estimated from the measured multiple fluorescence based on the estimated fluorescent dye's concentration function.

Abstract translation: 本发明的一个目的是提供一种荧光染料从多个荧光的浓度的估计方法，其中可以准确地估计荧光染料从多个荧光的荧光染料的浓度，并且在多个荧光中难以分离多个荧光 现有技术成为可能。 在荧光染料浓度从荧光染料浓度测量多个荧光的荧光染料浓度的估计方法中，对已知荧光染料浓度的荧光染料的光谱进行独立成分分析，得出独立成分的强度，回归分析为 通过使用独立成分的衍生强度作为变量来进行荧光染料的荧光染料的浓度函数的荧光染料的浓度的测定，荧光染料的浓度是已知的，荧光染料的浓度是根据测定的多个荧光估计的 染料的浓度功能。

公开(公告)号：US06895370B2

公开(公告)日：2005-05-17

申请号：US10890844

申请日：2004-07-09

Applicant: Raymond M. Castellane ,  Bartley P. Durst ,  Falih H. Ahmad

Inventor： Raymond M. Castellane ,  Bartley P. Durst ,  Falih H. Ahmad

IPC: G06F11/32 ,  G06F15/00 ,  G06F19/00

CPC classification number: G01N21/94 ,  G01N21/93 ,  G01N2201/1293

Abstract: Minute amounts of material, such as a contaminant, are detected, classified and located using a single procedure that eliminates the need for using complex and sometimes redundant instrumentation setups, multiple (and sometimes overlapping) analytic processes, or both. In one embodiment, a series of processing steps enables one to detect, classify, and localize minute amounts of particular elements, e.g., contaminants, in material being tested. Data sets, suitable for characterizing components of samples at least spectrally and spatially, are collected from at least one uncontaminated sample of material (the “baseline” or “control”) and a sample of material under test (MUT) that may contain contaminants. Comparison of these data sets, using the procedures of the present invention, enables ready classification of minute amounts of material in any sample. The present invention may be used for liquids, solids, and gases, with specific application to gels, pastes, hard powders, soft powders, films, inorganics, and pharmaceuticals.

Abstract translation: 使用单一程序检测，分类和定位分数量的材料，例如污染物，无需使用复杂且有时冗余的仪器设置，多个（有时是重叠的）分析过程或两者。 在一个实施例中，一系列处理步骤使得能够在被测试的材料中检测，分类和定位微量的特定元素，例如污染物。 从至少一个未受污染的材料样品（“基线”或“对照”）和可能含有污染物的待测物质样品（MUT）收集适用于表征至少在光谱和空间上的样品组分的数据集。 使用本发明的方法对这些数据集的比较使得能够对任何样品中的微量材料进行分类。 本发明可用于液体，固体和气体，特别适用于凝胶，糊剂，硬粉末，软粉末，膜，无机物和药物。