METHODS, STORAGE MEDIUMS, AND SYSTEMS FOR ANALYZING PARTICLE QUANTITY AND DISTRIBUTION WITHIN AN IMAGING REGION OF AN ASSAY ANALYSIS SYSTEM AND FOR EVALUATING THE PERFORMANCE OF A FOCUSING ROUTING PERFORMED ON AN ASSAY ANALYSIS SYSTEM
    1.
    发明申请
    METHODS, STORAGE MEDIUMS, AND SYSTEMS FOR ANALYZING PARTICLE QUANTITY AND DISTRIBUTION WITHIN AN IMAGING REGION OF AN ASSAY ANALYSIS SYSTEM AND FOR EVALUATING THE PERFORMANCE OF A FOCUSING ROUTING PERFORMED ON AN ASSAY ANALYSIS SYSTEM 审中-公开
    方法,存储媒体和系统,用于分析测量分析系统的成像区域中的粒子数量和分布,并评估在测定分析系统上执行的聚焦路由的性能

    公开(公告)号:WO2012009617A3

    公开(公告)日:2012-05-10

    申请号:PCT/US2011044152

    申请日:2011-07-15

    Inventor: ARAB NICOLAS

    Abstract: Methods, storage mediums and systems (MS&S) are provided which successively image an imaging region of an assay analysis system (AAS) as particles are loaded into the imaging region, generate a frequency spectrum of each image via a discrete Fourier transform, integrate a same coordinate portion of each frequency spectrum and terminate the loading of particles upon computing an integral which meets preset criterion. In addition, MS&S are provided which send a signal indicative of whether enough particles are in an imaging region for further processes by an AAS based on the magnitude of integral calculated from an image's frequency spectrum. MM&S are also provided such that the steps of generating a frequency spectrum of each image and integrating a portion of each frequency spectrum are replaced by generating a convolved spatial image with a filter kernel and integrating a same coordinate portion of each convolved spatial image.

    Abstract translation: 提供方法,存储介质和系统(MS&S),其随着颗粒被加载到成像区域中,连续地成像测定分析系统(AAS)的成像区域,通过离散傅里叶变换产生每个图像的频谱, 每个频谱的坐标部分,并在计算符合预设标准的积分时终止粒子的加载。 另外,提供MS&S,其发送指示基于从图像的频谱计算的积分的大小,是否足够的粒子在成像区域中的AAS的进一步处理的信号。 还提供MM&S,使得通过用滤波器核生成卷积空间图像并对每个卷积空间图像的相同坐标部分进行积分来代替产生每个图像的频谱并对每个频谱的一部分进行积分的步骤。

    APPARATUS, SYSTEM, AND METHOD FOR IMAGE NORMALIZATION USING A GAUSSIAN RESIDUAL OF FIT SELECTION CRITERIA
    2.
    发明申请
    APPARATUS, SYSTEM, AND METHOD FOR IMAGE NORMALIZATION USING A GAUSSIAN RESIDUAL OF FIT SELECTION CRITERIA 审中-公开
    装置,系统和使用高斯选择标准的GAUSSIAN残留图像正规化的方法

    公开(公告)号:WO2013188857A2

    公开(公告)日:2013-12-19

    申请号:PCT/US2013046035

    申请日:2013-06-14

    Applicant: LUMINEX CORP

    Abstract: An apparatus and method for image normalization using a Gaussian residual of fit selection criteria. The method may include acquiring a two-dimensional image of a plurality of particles, where the plurality of particles comprises a plurality of calibration particles, and identifying a calibration particle by correlating a portion of the image corresponding to the calibration particle to a mathematical model (e.g. Gaussian fit). The measured intensity of the calibration particle may then be used to normalize the intensity of the image.

    Abstract translation: 一种使用高斯残差拟合选择标准进行图像归一化的装置和方法。 该方法可以包括获取多个粒子的二维图像,其中多个粒子包括多个校准粒子,以及通过将对应于校准粒子的图像的一部分与数学模型相关来识别校准粒子( 例如高斯拟合)。 然后可以将校准颗粒的测量强度用于归一化图像的强度。

    APPARATUS AND METHODS FOR MULTI-STEP CHANNEL EMULSIFICATION

    公开(公告)号:CA2979415A1

    公开(公告)日:2016-09-22

    申请号:CA2979415

    申请日:2016-03-15

    Applicant: LUMINEX CORP

    Abstract: Methods and devices for forming droplets are provided. In certain embodiment's, the methods and devices form droplets having different diameters. Exemplary embodiment's of the present disclosure relate to systems and methods for forming droplets, including a multi-step microchannel emulsification device. One embodiment provides an emulsification device comprising: a channel having an inlet portion; a first step in fluid communication with the inlet portion; a second step in fluid communication with the first step; and a third step in fluid communication with the second step.

    APPARATUS, SYSTEM, AND METHOD FOR IMAGE NORMALIZATION USING A GAUSSIAN RESIDUAL OF FIT SELECTION CRITERIA

    公开(公告)号:CA2876903C

    公开(公告)日:2020-07-14

    申请号:CA2876903

    申请日:2013-06-14

    Applicant: LUMINEX CORP

    Abstract: An apparatus and method for image normalization using a Gaussian residual of fit selection criteria. The method may include acquiring a two-dimensional image of a plurality of particles, where the plurality of particles comprises a plurality of calibration particles, and identifying a calibration particle by correlating a portion of the image corresponding to the calibration particle to a mathematical model (e.g. Gaussian fit). The measured intensity of the calibration particle may then be used to normalize the intensity of the image.

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