WO2007035840B1 - Methods and systems for image data processing - Google Patents

Methods and systems for image data processing

Info

Publication number
WO2007035840B1
WO2007035840B1 PCT/US2006/036733 US2006036733W WO2007035840B1 WO 2007035840 B1 WO2007035840 B1 WO 2007035840B1 US 2006036733 W US2006036733 W US 2006036733W WO 2007035840 B1 WO2007035840 B1 WO 2007035840B1
Authority
WO
WIPO (PCT)
Prior art keywords
image
pixels
optical parameter
program instructions
determining
Prior art date
Application number
PCT/US2006/036733
Other languages
French (fr)
Other versions
WO2007035840A2 (en
WO2007035840A3 (en
Inventor
Wayne D Roth
Original Assignee
Luminex Corp
Wayne D Roth
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Luminex Corp, Wayne D Roth filed Critical Luminex Corp
Priority to EP17168644.7A priority Critical patent/EP3236234B1/en
Priority to JP2008532362A priority patent/JP5037511B2/en
Priority to EP22172377.8A priority patent/EP4071458A1/en
Priority to CA2623130A priority patent/CA2623130C/en
Priority to EP06803948.6A priority patent/EP1929274B1/en
Publication of WO2007035840A2 publication Critical patent/WO2007035840A2/en
Publication of WO2007035840A3 publication Critical patent/WO2007035840A3/en
Publication of WO2007035840B1 publication Critical patent/WO2007035840B1/en
Priority to KR1020087009141A priority patent/KR101264379B1/en

Links

Classifications

    • G01N15/1433—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • G06V20/695—Preprocessing, e.g. image segmentation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G01N15/1456—Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10064—Fluorescence image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20021—Dividing image into blocks, subimages or windows
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30072—Microarray; Biochip, DNA array; Well plate

Abstract

Methods, storage mediums, and systems for image data processing are provided. Embodiments for the methods, storage mediums, and systems include configurations to perform one or more of the following steps: background signal measurement, particle identification using classification dye emission and cluster rejection, inter-image alignment, inter-image particle correlation, fluorescence integration of reporter emission, and image plane normalization.

Claims

AMENDED CLAIMS received by the International Bureau on 22 October 2007
(22.10.2007)
1. A computer-implemented method, comprising: quantifying, within an image, an occupancy of particles having fluorescence-material associated therewith; separating the image into an array of subsections; determining a statistical value of an optical parameter measured for a particular set of pixels within a subsection, wherein the particular set of pixels is selected based upon the occupancy of particles within the image relative to a predetermined threshold; and assigning the determined statistical value as background signal for the corresponding subsection.
2. The computer-implemented method of claim 1, wherein the step of quantifying tho occupancy of particles within the image comprises determining the occupancy of particles within the image is less than a predetermined threshold, and wherein the step of determining the statistical value of the optical parameter comprises determining the statistical value of the optical parameter among all pixels within the subsection.
4. The computer-implemented method of claim 2, wherein the step of quantifying the occupancy of particles within the image comprises determining the occupancy of particles within the image is less than approximately 50%.
5. The computer-implemented method of claim 1 , wherein the step of quantifying the occupancy of particles within the image comprises determining the occupancy of particles within the image is greater than or equal to a first predetermined threshold, wherein the method further comprises identifying pixels within the subsection that exhibit an optical parameter value above a second predetermined threshold prior to the step of determining the statistical value of the optical parameter within the subsection, and wherein the step of determining the statistical value of the optical parameter for the particular set of pixels within the subsection comprises determining the statistical value of the optical parameter solely among a collection of pixels within the subsection which are not identified to exhibit an optical parameter value above the second predetermined threshold.
6. The eornpuler-implemenlcd method of claim 5, further comprising grouping the identified pixels with one or more pixels arranged immediately adjacent thereto prior to the step of determining the statistical value of the optical parameter, wherein the set of pixels used to determine the statistical value of the optical parameter exclude the grouped pixels.
8. The computer-implemented method of claim 5, wherein the step of quantifying the occupancy of particles comprises determining the occupancy of particles within the image is greater than or equal to approximately 50%.
9. The computer-implemented method of claim 1, wherein the steps of determining a statistical value of the optical parameter and assigning the determined statistical value as background signal are conducted for each of a plurality of the subsections in the array, and wherein the method further comprises applying a two-dimensional statistical filler on the array of subsections subsequent to assigning the determined statistical values as background signal for each of the plurality of subsections.
10. The computer-implemunted method of claim 1, wherein the step of determining the statistical value of the optical parameter comprises determining the median value of the optical parameter.
1 1. A storage medium comprising program instructions which are executable by a processor for; analyzing an image of particles having fluorescence-material associated therewith to identify one or more pixels within the image that exhibit an optical parameter value above a first predetermined threshold; determining locations within sets of the one or more identified pixels that respectively exhibit maximum values for the optical parameter within the sets; computing a rate of intensity change of the optical parameter for a plurality of pixels surrounding at least one of the locations; and accepting or rejecting the plurality of pixels for further evaluation based upon the computed rate of intensity change.
12. The storage medium of claim 11, wherein the program instructions for accepting or rejecting the plurality of pixels comprise: accepting the plurality of pixels for further evaluation upon computing the rate of intensity change is greater than or equal to a second predetermined threshold distinct from the first predetermined threshold; and rejecting the plurality of pixels for further evaluation upon computing the rate of intensity change is less than the second predetermined threshold.
1 3 The storage medium of claim 11, wherein the program instructions for computing the rate of intensity change comprise program instructions for: summing values of the optical parameter for a first set of the plurality of pixels arranged within a first predetermined radius surrounding the at least one location; summing values of the optical parameter for a second set of the plurality of pixels arranged within a second predetermined radius surrounding the at least one location, wherein the second predetermined radius is larger than the first predetermined radius; and determining a ratio of the summed values respectively computed for the first and second sets of pixels,
14. The storage medium of claim 13, wherein the first predetermined radius is approximately equal to a projected diameter of a single particle within the image, wherein the projected diameter is based on the component configurations of a system used to image the particles.
15. The storage medium of claim 13, wherein the second predetermined radius is approximately 1.5 times greater than a projected diameter of a single particle within the image, wherein the projected diameter is based on the component configurations of a system used to image the particles.
16. The storage medium or claim 11 , wherein the program instructions for determining the locations comprise program instructions for ascertaining peak pixels among the sets of one or more identified pixels that respectively exhibit maximum values for the optical parameter.
17. The storage medium of claim 16, wherein the program instructions for determining the locations further comprise program instructions for computing a centroid location within at least one of the sets of one or more identified pixels based upon the values of the optical parameter within the peak pixel corresponding to the at least one set and within pixels neighboring the peak pixel contained by a second predetermined radius surrounding the peak pixel.
18. This storage medium of claim 17, wherein the program instructions for determining the location further comprise program instructions for assigning the centroid location as the location exhibiting the maximum value for the optical parameter within the at least one set upon determining a dimension of the centroid location is greater than approximately 50% of a pixel width within the image,
19. The storage medium of claim 16, further comprising program instructions for: computing a distance between two of the peak pixels; and rejecting for further evaluation a set of pixels corresponding to one of the two peak pixels upon computing the distance is less than a second predetermined threshold.
20. A system configured to acquire and process image data, comprising: an imaging subsystem configured to; image, at different wavelength bands, particles disposed within the imaging subsystem; and acquire data corresponding to omissions of imaged particles; and a storage medium comprising program instructions which are executable by a processor for: storing data acquired for multiple images of the particles, wherein each of the multiple images corresponds to a different wavelength band; creating a composite image of the multiple images; and manipulating the coordinates of at least one of the multiple images such that spots corresponding to the particles within each of the multiple images converge within an ensuing composite image.
21. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for performing at least one of an orthogonal offset of the coordinates and rotation of the at least one of the multiple image,
22. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for; algorithmically determining an offset to modify coordinates of at least one of the multiple images such that an amount of color variance among the spots in an ensuing composite image is reduced relative to a preceding composite image; adjusting the coordinates of the at least one image by the predetermined offset; and creating a different composite image of the multiple images subsequent to the step of adjusting the coordinates of the at least one image.
23. The system of claim 22, wherein the program instructions for manipulating the coordinate parameters further comprise program instructions for: determining the color variance among spots in the different composite image; and iterating the steps of algorithmically determining an offset, adjusting the coordinates of the at least one image, creating a different composite image, and determining the color variance among spots until the amount of color variance among the spots of a composite image is less than a predetermined error allowance for the algorithmically determined offset
24. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for: adjusting coordinates of at least one image by a predetermined offset; creating a different composite image of the multiple images subsequent to the step of adjusting the coordinates of the at least one image; computing an aggregate error or mean squared difference of intensities among pixels corresponding to spots within the different composite image; repeating the steps of adjusting the coordinates of the at least one image, creating a different composite image, and computing the aggregate error or mean squared difference of intensities with different predetermined offsets for a predetermined number of iterations; comparing the computed values of aggregate error or mean squared difference of intensities for each of the different composite images; and saving offset values for each image having adjusted coordinates corresponding to the composite image having the smallest aggregate error or mean squared difference of intensities.
25. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for: adjusting coordinates of at least one image by a predetermined offset; creating a different composite image of the multiple images subsequent to the step of adjusting the coordinates of the at least one image; computing an aggregate error or mean squared difference among locations of spots within the different composite image; repeating the steps of adjusting the coordinates of the at least one image, creating a different composite image, and computing the aggregate error or mean squared difference of spot locations with different predetermined offsets for a predetermined number of iterations; comparing the computed values of aggregate error or mean squared difference of the spot locations for cnch of the different composite images; and saving offset values for each image having adjusted coordinates corresponding to lhe composite image having the smallest aggregate error or mean squared difference of spot locations.
26. The system of claim 20, wherein the storage medium further comprises program instructions which are executable by a processor for: determining whether a particle imaged at one wavelength band used to classify the particles disposed within the imaging subsystem is further imaged at a different wavelength band used to classify the particles; accepting the particle for further evaluation upon determining the particle is imaged at the different wavelength band; and rejecting the particle for further evaluation upon determining the particle is not imaged at the different wavelength band.
27. A computer-implemented method, comprising; analyzing a first image of a first set of particles having a uniform concentration of fluorescence- material associated therewith to identify one or more pixels within the first image that exhibit an optical parameter value above a first predetermined threshold; categorizing, within respective subsections of the first image, collections of pixels identified during the step of analyzing the first image; developing for each respective subsection within the first image a statistic representative of the level of the optical parameter for the collections of pixels categorized thereto; analyzing a second image of particles having an unknown concentration of fluorescence-material associated therewith to identify one or more pixels within the second image that exhibit an optical parameter value above the first predetermined threshold; separating the second image to have subsections with dimensions that are substantially equal to the subsections in the first image; categorizing, within respective subsections of the second image, collections of pixels identified during the step of analyzing the second image; and computing a normalized value for the optical parameter by dividing the optical parameter value for each of the pixels identified during the step of analyzing the second image by the statistic developed for the corresponding first image subsection .
28. The computer-implemented method of claim 27, further comprising: analysing a third image of the particles having the uniform concentration of fluorescence-material associated therewith to identify one or more pixels within the third image that exhibit an optical parameter value above the first predetermined threshold, wherein the third image is formed using an illumination source of a different wavelength than the first image; separating the third image to have subsections with dimensions that are substantially equal to the subsections in the first image; categorizing, within respective subsections of the third image, collections of pixels identified during the step of analyzing the third image; developing for each respective subsection within the third image a statistic representative of the level of the optical parameter for the collections of pixels categorized thereto; saving the statistics developed for each respective subsection of the first and third images in matrices specific to the wavelengths used to form the first and third images; and wherein the step of computing the normalized value comprises dividing the optical parameter value for each of the pixels identified during the step of analysing the second image by the statistics developed for the corresponding subsections of the first and third images.
29. The computer-implemented method of claim 27, further comprising: prior to the step of analyzing the second image, analyzing a third image of a different set of particles having a uniform concentration of fluorescence-material associated therewith to identify one or more pixels within the third image that exhibit an optical parameter value above the first predetermined threshold; separating the third image to have subsections with dimensions that are substantially equal to the subsections in the first image; categorizing, within respective subsections of the third image, collections of pixels identified during the step of analyzing the third image; developing for each respective subsection of the third image a statistic representative of the level of the optical parameter for the collections of pixels classified thereto; computing a mean of the statistics developed for each respective subsections of the first and third images; and wherein the step of computing the normalized value comprises dividing the optical parameter value for each of the pixels identified during the step of analyzing the second image by the computed mean of the statistics developed for the corresponding subsections of the first and third images,
30. The computer-implemented method of claim 29, further comprising; computing a statistical value which is representative of all of the statistics developed for the respective subsections; and dividing a predetermined numerical value associated with a level of the optical parameter associated with the first and third sets of particles having uniform concentrations of fluorescence-material associated therewith by the computed statistical value to compute a calibrator value.
31. The computer-implemented method of claim 30, further comprising multiplying the normalized value by the calibrator value.
32. The storage medium of claim 13, wherein the program instructions for determining the ratio of the summed values comprise program instructions for dividing the summed values computed for the second set of pixels by the summed values computed for the first set of pixels, and wherein the program instructions for accepting or rejecting the plurality of pixels comprise program instructions for: accepting tho plurality of pixels for Further evaluation upon determining the ratio differs from a set value by an amount less than or equal to a second predetermined threshold distinct from the first predetermined threshold; and rejecting the plurality of pixels for further evaluation upon determining the ratio differs from the set value by an amount greater than the second predetermined threshold.
33. The storage medium of claim 13, wherein the program instructions for determining the ratio of the summed values comprise program instructions for dividing me summed values computed for the first set of pixels by the summed values computed for the second set of pixels, and wherein the program instructions for accepting or rejecting the plurality of pixels comprise program instructions for: accepting the plurality of pixels for further evaluation upon determining the ratio differs from a set value by an amount greater than or equal to a second predetermined threshold distinct from the first predetermined threshold; and rejecting the plurality of pixels for further evaluation upon determining the ratio differs from the set value by an amount less than the second predetermined threshold.
34. The computer-implemented method of clai m 27 , further comprising: the second image being of a second set of particles; analyzing a third image of the first set of particles having the uniform concentration of fluorescence- material associated therewith to identify one or more pixels within the third image that exhibit an optical parameter value above the first predetermined threshold, wherein the third image is formed using an illumination source of a different wavelength than the first image; analyzing a fourth image of said second set of particles; and
Wherein the fourth image is formed using an illumination source of a different wavelength than the second image,
PCT/US2006/036733 2005-09-21 2006-09-21 Methods and systems for image data processing WO2007035840A2 (en)

Priority Applications (6)

Application Number Priority Date Filing Date Title
EP17168644.7A EP3236234B1 (en) 2005-09-21 2006-09-21 Methods and systems for image data processing
JP2008532362A JP5037511B2 (en) 2005-09-21 2006-09-21 Image data processing method and system
EP22172377.8A EP4071458A1 (en) 2005-09-21 2006-09-21 Methods and systems for image data processing
CA2623130A CA2623130C (en) 2005-09-21 2006-09-21 Methods and systems for image data processing
EP06803948.6A EP1929274B1 (en) 2005-09-21 2006-09-21 Methods and systems for image data processing
KR1020087009141A KR101264379B1 (en) 2005-09-21 2008-04-16 Methods and systems for image data processing

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US71901005P 2005-09-21 2005-09-21
US60/719,010 2005-09-21

Publications (3)

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WO2007035840A2 WO2007035840A2 (en) 2007-03-29
WO2007035840A3 WO2007035840A3 (en) 2007-10-04
WO2007035840B1 true WO2007035840B1 (en) 2007-12-06

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PCT/US2006/036733 WO2007035840A2 (en) 2005-09-21 2006-09-21 Methods and systems for image data processing

Country Status (8)

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US (8) US8031918B2 (en)
EP (4) EP4071458A1 (en)
JP (3) JP5037511B2 (en)
KR (1) KR101264379B1 (en)
CN (3) CN102621053B (en)
CA (3) CA2623130C (en)
HK (1) HK1173777A1 (en)
WO (1) WO2007035840A2 (en)

Families Citing this family (101)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1859330B1 (en) 2005-01-28 2012-07-04 Duke University Apparatuses and methods for manipulating droplets on a printed circuit board
CA2606750C (en) 2005-05-11 2015-11-24 Nanolytics, Inc. Method and device for conducting biochemical or chemical reactions at multiple temperatures
EP4071458A1 (en) 2005-09-21 2022-10-12 Luminex Corporation Methods and systems for image data processing
US20140193807A1 (en) 2006-04-18 2014-07-10 Advanced Liquid Logic, Inc. Bead manipulation techniques
US9476856B2 (en) 2006-04-13 2016-10-25 Advanced Liquid Logic, Inc. Droplet-based affinity assays
US7901947B2 (en) 2006-04-18 2011-03-08 Advanced Liquid Logic, Inc. Droplet-based particle sorting
US8637324B2 (en) 2006-04-18 2014-01-28 Advanced Liquid Logic, Inc. Bead incubation and washing on a droplet actuator
US8389297B2 (en) 2006-04-18 2013-03-05 Duke University Droplet-based affinity assay device and system
US7439014B2 (en) * 2006-04-18 2008-10-21 Advanced Liquid Logic, Inc. Droplet-based surface modification and washing
US8716015B2 (en) 2006-04-18 2014-05-06 Advanced Liquid Logic, Inc. Manipulation of cells on a droplet actuator
US10078078B2 (en) 2006-04-18 2018-09-18 Advanced Liquid Logic, Inc. Bead incubation and washing on a droplet actuator
US8809068B2 (en) 2006-04-18 2014-08-19 Advanced Liquid Logic, Inc. Manipulation of beads in droplets and methods for manipulating droplets
US8658111B2 (en) 2006-04-18 2014-02-25 Advanced Liquid Logic, Inc. Droplet actuators, modified fluids and methods
US8980198B2 (en) * 2006-04-18 2015-03-17 Advanced Liquid Logic, Inc. Filler fluids for droplet operations
WO2007123908A2 (en) 2006-04-18 2007-11-01 Advanced Liquid Logic, Inc. Droplet-based multiwell operations
WO2009111769A2 (en) 2008-03-07 2009-09-11 Advanced Liquid Logic, Inc. Reagent and sample preparation and loading on a fluidic device
US8296088B2 (en) 2006-06-02 2012-10-23 Luminex Corporation Systems and methods for performing measurements of one or more materials
US8889347B2 (en) * 2006-06-02 2014-11-18 Luminex Corporation Systems and methods for performing measurements of one or more materials
US8009889B2 (en) * 2006-06-27 2011-08-30 Affymetrix, Inc. Feature intensity reconstruction of biological probe array
EP2099930B1 (en) * 2006-12-13 2015-02-18 Luminex Corporation Systems and methods for multiplex analysis of pcr in real time
US8685344B2 (en) * 2007-01-22 2014-04-01 Advanced Liquid Logic, Inc. Surface assisted fluid loading and droplet dispensing
CN101627308B (en) * 2007-02-09 2013-08-14 先进流体逻辑公司 Droplet actuator devices and methods employing magnetic beads
WO2008101194A2 (en) 2007-02-15 2008-08-21 Advanced Liquid Logic, Inc. Capacitance detection in a droplet actuator
EP2837692A1 (en) 2007-03-22 2015-02-18 Advanced Liquid Logic, Inc. Enzymatic assays for a droplet actuator
AU2008237017B2 (en) * 2007-04-10 2013-10-24 Advanced Liquid Logic, Inc. Droplet dispensing device and methods
WO2009002920A1 (en) 2007-06-22 2008-12-31 Advanced Liquid Logic, Inc. Droplet-based nucleic acid amplification in a temperature gradient
US8591830B2 (en) * 2007-08-24 2013-11-26 Advanced Liquid Logic, Inc. Bead manipulations on a droplet actuator
WO2009032863A2 (en) * 2007-09-04 2009-03-12 Advanced Liquid Logic, Inc. Droplet actuator with improved top substrate
US8171777B2 (en) * 2007-09-17 2012-05-08 Adam Richard Schilffarth Systems, storage mediums, and methods for identifying particles in flow
US8460528B2 (en) * 2007-10-17 2013-06-11 Advanced Liquid Logic Inc. Reagent storage and reconstitution for a droplet actuator
US20100236928A1 (en) * 2007-10-17 2010-09-23 Advanced Liquid Logic, Inc. Multiplexed Detection Schemes for a Droplet Actuator
US20100236929A1 (en) * 2007-10-18 2010-09-23 Advanced Liquid Logic, Inc. Droplet Actuators, Systems and Methods
WO2009076414A2 (en) * 2007-12-10 2009-06-18 Advanced Liquid Logic, Inc. Droplet actuator configurations and methods
JP5462183B2 (en) 2007-12-23 2014-04-02 アドヴァンスト リキッド ロジック インコーポレイテッド Droplet actuator configuration and method for directing droplet motion
US20090170214A1 (en) * 2007-12-27 2009-07-02 Luminex Corporation Luminescent Reporter Modality for Analyzing an Assay
JP5550182B2 (en) 2008-01-07 2014-07-16 ルミネックス コーポレーション Method for isolation and enumeration of cells from a composite sample matrix
WO2009089254A1 (en) * 2008-01-07 2009-07-16 Luminex Corporation Immunomagnetic capture and imaging of biological targets
US8852952B2 (en) 2008-05-03 2014-10-07 Advanced Liquid Logic, Inc. Method of loading a droplet actuator
US20110097763A1 (en) * 2008-05-13 2011-04-28 Advanced Liquid Logic, Inc. Thermal Cycling Method
EP2286228B1 (en) * 2008-05-16 2019-04-03 Advanced Liquid Logic, Inc. Droplet actuator devices and methods for manipulating beads
CN104732199B (en) * 2008-07-17 2018-06-05 卢米耐克斯公司 For configuring the method for the specification area in classification matrix and storage medium
US8877512B2 (en) * 2009-01-23 2014-11-04 Advanced Liquid Logic, Inc. Bubble formation techniques using physical or chemical features to retain a gas bubble within a droplet actuator
US8926065B2 (en) 2009-08-14 2015-01-06 Advanced Liquid Logic, Inc. Droplet actuator devices and methods
US8846414B2 (en) 2009-09-29 2014-09-30 Advanced Liquid Logic, Inc. Detection of cardiac markers on a droplet actuator
WO2011057197A2 (en) 2009-11-06 2011-05-12 Advanced Liquid Logic, Inc. Integrated droplet actuator for gel electrophoresis and molecular analysis
CA2781824A1 (en) * 2009-11-30 2011-06-03 Bio-Rad Laboratories Inc. Bead reader
EP2516669B1 (en) 2009-12-21 2016-10-12 Advanced Liquid Logic, Inc. Enzyme assays on a droplet actuator
US9500644B2 (en) * 2010-02-23 2016-11-22 Luminex Corporation Particle populations and assays having varying amounts of magnetic material and particle concentrations among different subsets of particles and methods for processing assays having such particle populations
EP2539450B1 (en) 2010-02-25 2016-02-17 Advanced Liquid Logic, Inc. Method of making nucleic acid libraries
WO2011126892A2 (en) 2010-03-30 2011-10-13 Advanced Liquid Logic, Inc. Droplet operations platform
US9011662B2 (en) 2010-06-30 2015-04-21 Advanced Liquid Logic, Inc. Droplet actuator assemblies and methods of making same
US8274656B2 (en) 2010-06-30 2012-09-25 Luminex Corporation Apparatus, system, and method for increasing measurement accuracy in a particle imaging device
US8767069B2 (en) * 2010-06-30 2014-07-01 Luminex Corporation Apparatus, system, and method for increasing measurement accuracy in a particle imaging device using light distribution
EP2593771B1 (en) 2010-07-16 2019-09-04 Luminex Corporation 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
JP5682976B2 (en) * 2010-09-17 2015-03-11 国立大学法人東北大学 Method for determining the effectiveness of pharmaceuticals containing antibodies as components
EP2641097A4 (en) 2010-11-17 2016-09-07 Capacitance detection in a droplet actuator
CN102288530B (en) * 2010-12-29 2014-05-14 天津炜辐医疗科技有限公司 Time delay integral imaging system for measuring diffraction image of moving particle
US9134241B2 (en) * 2011-04-11 2015-09-15 Li-Cor, Inc. Differential scan imaging systems and methods
EP2705374A4 (en) 2011-05-02 2014-11-12 Advanced Liquid Logic Inc Molecular diagnostics platform
WO2012154745A2 (en) 2011-05-09 2012-11-15 Advanced Liquid Logic, Inc. Microfluidic feedback using impedance detection
EP2707724A4 (en) 2011-05-10 2015-01-21 Advanced Liquid Logic Inc Enzyme concentration and assays
AU2012279420A1 (en) 2011-07-06 2014-01-30 Advanced Liquid Logic Inc Reagent storage on a droplet actuator
US8901043B2 (en) 2011-07-06 2014-12-02 Advanced Liquid Logic, Inc. Systems for and methods of hybrid pyrosequencing
WO2013009927A2 (en) 2011-07-11 2013-01-17 Advanced Liquid Logic, Inc. Droplet actuators and techniques for droplet-based assays
WO2013016413A2 (en) 2011-07-25 2013-01-31 Advanced Liquid Logic Inc Droplet actuator apparatus and system
WO2013059338A1 (en) * 2011-10-18 2013-04-25 Luminex Corporation Methods and systems for image data processing
WO2013078216A1 (en) 2011-11-21 2013-05-30 Advanced Liquid Logic Inc Glucose-6-phosphate dehydrogenase assays
US9223317B2 (en) 2012-06-14 2015-12-29 Advanced Liquid Logic, Inc. Droplet actuators that include molecular barrier coatings
EP2861969B1 (en) 2012-06-15 2022-08-03 Luminex Corporation Method for image normalization using a gaussian residual of fit selection criteria
CA2877950C (en) 2012-06-27 2021-06-22 Advanced Liquid Logic Inc. Techniques and droplet actuator designs for reducing bubble formation
WO2014062551A1 (en) 2012-10-15 2014-04-24 Advanced Liquid Logic, Inc. Digital microfluidics cartridge and system for operating a flow cell
US9135515B2 (en) * 2012-10-22 2015-09-15 Qiagen Gaithersburg, Inc. Automated pelletized sample vision inspection apparatus and methods
US8988663B2 (en) * 2013-01-22 2015-03-24 Raytheon Company Laser range finding
US9146248B2 (en) 2013-03-14 2015-09-29 Intelligent Bio-Systems, Inc. Apparatus and methods for purging flow cells in nucleic acid sequencing instruments
US9212976B2 (en) 2013-03-15 2015-12-15 Qiagen Gaithersburg, Inc. Vision-guided aspiration apparatus and methods
US9591268B2 (en) 2013-03-15 2017-03-07 Qiagen Waltham, Inc. Flow cell alignment methods and systems
US10124351B2 (en) 2013-08-13 2018-11-13 Advanced Liquid Logic, Inc. Methods of improving accuracy and precision of droplet metering using an on-actuator reservoir as the fluid input
CN105916689A (en) 2013-08-30 2016-08-31 Illumina公司 Manipulation of droplets on hydrophilic or variegated-hydrophilic surfaces
CA2946869A1 (en) 2014-04-24 2015-10-29 Immusant, Inc. Methods for diagnosing celiac disease using circulating cytokines/chemokines
EP3680333A1 (en) 2014-04-29 2020-07-15 Illumina, Inc. Multiplexed single cell expression analysis using template switch and tagmentation
US9251427B1 (en) * 2014-08-12 2016-02-02 Microsoft Technology Licensing, Llc False face representation identification
WO2016081869A2 (en) 2014-11-21 2016-05-26 Immusant, Inc. Peptides for use in treatment and diagnosis of type 1 diabetes
SG11201706352QA (en) * 2015-02-06 2017-09-28 Life Technologies Corp System and methods for calibrating binding dyes
WO2016154038A1 (en) 2015-03-20 2016-09-29 Illumina, Inc. Fluidics cartridge for use in the vertical or substantially vertical position
CA3172078A1 (en) 2015-08-28 2017-03-09 Illumina, Inc. Nucleic acid sequence analysis from single cells
ES2786974T3 (en) 2016-04-07 2020-10-14 Illumina Inc Methods and systems for the construction of standard nucleic acid libraries
JP6913697B2 (en) 2016-06-24 2021-08-04 ベックマン コールター， インコーポレイテッド Image Atlas System and Method
US10324041B2 (en) 2016-12-21 2019-06-18 Abbott Japan Co., Ltd. Optical imaging system using lateral illumination for digital assays
US11047854B2 (en) 2017-02-06 2021-06-29 Abbott Japan Llc Methods for reducing noise in signal-generating digital assays
WO2019018040A1 (en) 2017-04-24 2019-01-24 Trustees Of Princeton University Anisotropic twicing for single particle reconstruction using autocorrelation analysis
JP6853469B2 (en) * 2017-04-28 2021-03-31 国立研究開発法人海洋研究開発機構 Integrated system and integrated method
CN111095075B (en) * 2017-06-13 2023-04-28 普林斯顿大学理事会 Full-automatic template-free particle pick-up for electron microscopy
CN112041459A (en) 2018-01-29 2020-12-04 圣祖德儿童研究医院 Nucleic acid amplification method
EP3762758A2 (en) * 2018-03-07 2021-01-13 Wöhler, Christian Imaging apparatuses, systems and methods
EP3788348B1 (en) 2018-05-02 2023-08-02 Corning Research & Development Corporation Methods for detection of contaminants on optical fiber connectors
KR102547321B1 (en) * 2018-06-01 2023-06-23 삼성전자주식회사 Image display device and operating method for the same
CN108805887B (en) * 2018-06-19 2021-07-23 北京航空航天大学 Modeling method for strip-shaped single-particle imaging noise
KR102039016B1 (en) * 2018-09-13 2019-10-31 황준철 Concentration monitoring system and method
EP3719477B1 (en) * 2019-04-03 2023-01-18 Mecwins, S.A. Method for optically detecting biomarkers
CA3176615A1 (en) 2020-03-30 2021-10-07 Illumina, Inc. Methods and compositions for preparing nucleic acid libraries
US11709124B2 (en) * 2020-07-13 2023-07-25 Honeywell International Inc. Particle sensor sample area qualification without a physical slit

Family Cites Families (85)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0786455B2 (en) * 1986-07-18 1995-09-20 興和株式会社 Particle measuring method and apparatus
US5206699A (en) * 1988-05-06 1993-04-27 Gersan Establishment Sensing a narrow frequency band of radiation and gemstones
US6610256B2 (en) * 1989-04-05 2003-08-26 Wisconsin Alumni Research Foundation Image processing and analysis of individual nucleic acid molecules
US5016173A (en) * 1989-04-13 1991-05-14 Vanguard Imaging Ltd. Apparatus and method for monitoring visually accessible surfaces of the body
US6040138A (en) 1995-09-15 2000-03-21 Affymetrix, Inc. Expression monitoring by hybridization to high density oligonucleotide arrays
US5107422A (en) 1989-10-02 1992-04-21 Kamentsky Louis A Method and apparatus for measuring multiple optical properties of biological specimens
US5162990A (en) 1990-06-15 1992-11-10 The United States Of America As Represented By The United States Navy System and method for quantifying macrophage phagocytosis by computer image analysis
US5579409A (en) * 1991-09-27 1996-11-26 E. I. Du Pont De Nemours And Company Methods for determining the exterior points of an object in a background
JPH05164687A (en) * 1991-12-18 1993-06-29 Hamamatsu Photonics Kk Ratio imaging apparatus
DE69331982T2 (en) * 1992-11-27 2003-01-23 Fuji Photo Film Co Ltd Method for adjusting the position of X-ray images
US6090555A (en) 1997-12-11 2000-07-18 Affymetrix, Inc. Scanned image alignment systems and methods
US5715334A (en) 1994-03-08 1998-02-03 The University Of Connecticut Digital pixel-accurate intensity processing method for image information enhancement
JP3347865B2 (en) 1994-03-17 2002-11-20 富士写真フイルム株式会社 How to align radiographic images
JPH07286952A (en) * 1994-04-19 1995-10-31 Hitachi Ltd Particle image analyzing device
EP0713086B1 (en) 1994-11-17 1999-04-14 Chemunex Apparatus and process for the detection and counting of rarely occurring mammalian cells
US5828766A (en) 1994-12-15 1998-10-27 Anthony Gallo Acoustics, Inc. Acoustic speaker system
US5981180A (en) 1995-10-11 1999-11-09 Luminex Corporation Multiplexed analysis of clinical specimens apparatus and methods
US5736330A (en) 1995-10-11 1998-04-07 Luminex Corporation Method and compositions for flow cytometric determination of DNA sequences
DE69638321D1 (en) 1995-10-11 2011-03-03 Luminex Corp SIMULTANEOUS MULTI-ANALYSIS OF CLINICAL SAMPLES
AU699519B2 (en) * 1995-10-23 1998-12-03 Cytometrics, Inc. Method and apparatus for reflected imaging analysis
US6165734A (en) * 1995-12-12 2000-12-26 Applied Spectral Imaging Ltd. In-situ method of analyzing cells
US5841148A (en) * 1996-02-02 1998-11-24 Fuji Photo Film Co., Ltd. Image processing apparatus
DE19629141A1 (en) 1996-07-19 1998-04-16 Bayer Ag Method and device for screening molecules for their individual binding behavior to at least one predetermined ligand
US6506564B1 (en) 1996-07-29 2003-01-14 Nanosphere, Inc. Nanoparticles having oligonucleotides attached thereto and uses therefor
US6449562B1 (en) 1996-10-10 2002-09-10 Luminex Corporation Multiplexed analysis of clinical specimens apparatus and method
US6416959B1 (en) * 1997-02-27 2002-07-09 Kenneth Giuliano System for cell-based screening
EP1439384B1 (en) 1997-02-27 2008-05-14 Cellomics, Inc. A system for screening biological cells
EP0985142A4 (en) 1997-05-23 2006-09-13 Lynx Therapeutics Inc System and apparaus for sequential processing of analytes
JPH11126259A (en) * 1997-06-02 1999-05-11 Matsushita Electric Ind Co Ltd Image detecting method, image detector, image processing method, image processor and medium
WO1999019515A1 (en) * 1997-10-14 1999-04-22 Luminex Corporation Precision fluorescently dyed particles and methods of making and using same
ATE239801T1 (en) * 1998-01-22 2003-05-15 Luminex Corp MICROPARTICLES WITH MULTIPLE FLUORESCENCE SIGNALS
AU4184099A (en) * 1998-05-14 1999-11-29 Luminex Corporation Zero dead time architecture and method for flow cytometer
AU3897999A (en) 1998-05-14 1999-11-29 Luminex Corporation Multi-analyte diagnostic system and computer implemented process for same
ATE292822T1 (en) 1998-11-13 2005-04-15 Cellomics Inc METHOD AND SYSTEM FOR EFFICIENTLY OBTAINING AND STORING EXPERIMENTAL DATA
GB9903555D0 (en) * 1999-02-16 1999-04-07 The Technology Partnership Plc Chemical and biological assay method and apparatus
JP2000299874A (en) 1999-04-12 2000-10-24 Sony Corp Signal processor, signal processing method, image pickup device and image pickup method
US6284465B1 (en) 1999-04-15 2001-09-04 Agilent Technologies, Inc. Apparatus, systems and method for locating nucleic acids bound to surfaces
US7151847B2 (en) 2001-02-20 2006-12-19 Cytokinetics, Inc. Image analysis of the golgi complex
US6876760B1 (en) 2000-12-04 2005-04-05 Cytokinetics, Inc. Classifying cells based on information contained in cell images
US6307959B1 (en) * 1999-07-14 2001-10-23 Sarnoff Corporation Method and apparatus for estimating scene structure and ego-motion from multiple images of a scene using correlation
US6687395B1 (en) 1999-07-21 2004-02-03 Surromed, Inc. System for microvolume laser scanning cytometry
US6986993B1 (en) * 1999-08-05 2006-01-17 Cellomics, Inc. System for cell-based screening
IL147793A0 (en) * 1999-08-05 2002-08-14 Cellomics Inc Optical system analysis of cells
DE60040603D1 (en) 1999-08-17 2008-12-04 Luminex Corp METHOD FOR ANALYZING A MULTIPLE OF SAMPLES OF VARIOUS ORIGIN ON AN ANALYTE
ATE324588T1 (en) 1999-08-17 2006-05-15 Luminex Corp ENCAPSULATION OF FLUORESCENT PARTICLES
AU2073801A (en) 1999-12-09 2001-06-18 Cellomics, Inc. A system for cell-based screening
TW461214B (en) * 2000-02-18 2001-10-21 Acer Peripherals Inc Progressive image processing method of graphic image
US20030198385A1 (en) * 2000-03-10 2003-10-23 Tanner Cameron W. Method apparatus for image analysis
US6545758B1 (en) 2000-08-17 2003-04-08 Perry Sandstrom Microarray detector and synthesizer
US6829376B2 (en) 2000-10-24 2004-12-07 Affymetrix, Inc. Computer software system, method, and product for scanned image alignment
US7050620B2 (en) * 2001-03-30 2006-05-23 Heckman Carol A Method of assaying shape and structural features in cells
WO2002086416A2 (en) 2001-04-25 2002-10-31 Amnis Corporation Method and apparatus for correcting crosstalk and spatial resolution for multichannel imaging
JP2002344978A (en) 2001-05-17 2002-11-29 Ichikawa Soft Laboratory:Kk Image processing unit
US6879708B2 (en) 2001-05-24 2005-04-12 Case Western Reserve University Planar particle/droplet size measurement technique using digital particle image velocimetry image data
JP4571763B2 (en) * 2001-07-18 2010-10-27 株式会社新川 Image processing apparatus and bonding apparatus
US20040071328A1 (en) * 2001-09-07 2004-04-15 Vaisberg Eugeni A. Classifying cells based on information contained in cell images
JP4749637B2 (en) * 2001-09-28 2011-08-17 オリンパス株式会社 Image analysis method, apparatus, and recording medium
CA2474036C (en) 2001-11-07 2012-09-25 S3I, Llc System and method for detecting and classifying biological particles
JP4043925B2 (en) 2001-12-05 2008-02-06 三菱レイヨン株式会社 Biological material microarray reader and method
US7133547B2 (en) 2002-01-24 2006-11-07 Tripath Imaging, Inc. Method for quantitative video-microscopy and associated system and computer software program product
KR20040105717A (en) 2002-02-14 2004-12-16 이뮤니베스트 코포레이션 Methods and algorithms for cell enumeration in a low-cost cytometer
JP4311607B2 (en) * 2002-05-27 2009-08-12 富士フイルム株式会社 Fluorescence diagnostic information generation method and apparatus
JP4291263B2 (en) 2002-05-28 2009-07-08 オウトジエノミクス・インコーポレーテツド Multi reagent pack
WO2003100380A2 (en) 2002-05-28 2003-12-04 Autogenomics, Inc. Integrated sample processing platform
US7236620B1 (en) * 2002-06-24 2007-06-26 Icad, Inc. Computer-aided detection methods in volumetric imagery
JP2004038728A (en) * 2002-07-05 2004-02-05 Noritsu Koki Co Ltd Image processing method, image processing program, and recording medium recording image processing program
AU2003252254A1 (en) 2002-07-26 2004-05-04 Olympus Corporation Image processing system
EP1565873B1 (en) * 2002-11-18 2013-06-05 International Remote Imaging Systems, Inc. Particle extraction for automatic flow microscope
US7063777B2 (en) 2002-12-12 2006-06-20 Aura Biosystems Inc. Dielectrophoretic particle profiling system and method
JP2004290119A (en) * 2003-03-27 2004-10-21 Sysmex Corp Method and apparatus for analyzing bacterium
ATE476908T1 (en) * 2003-04-18 2010-08-15 Medispectra Inc SYSTEM AND DIAGNOSTIC METHOD FOR OPTICAL DETECTION OF SUSPICIOUS AREAS IN A TISSUE SAMPLE
CN1180368C (en) * 2003-05-22 2004-12-15 上海交通大学 Image quality evaluating method for iris identification system
WO2005001436A1 (en) 2003-06-26 2005-01-06 The Secretary Of State For Defence Improvements to fluid borne particle analysers
US20050009032A1 (en) * 2003-07-07 2005-01-13 Cytokinetics, Inc. Methods and apparatus for characterising cells and treatments
US7362920B2 (en) * 2003-09-22 2008-04-22 Siemens Medical Solutions Usa, Inc. Method and system for hybrid rigid registration based on joint correspondences between scale-invariant salient region features
JP4102286B2 (en) * 2003-10-22 2008-06-18 シスメックス株式会社 Particle image analysis method and apparatus, program and recording medium
CN1259636C (en) 2003-12-31 2006-06-14 厦门大学 Red tide biological picture automatic identification device and identification method
US7456377B2 (en) * 2004-08-31 2008-11-25 Carl Zeiss Microimaging Ais, Inc. System and method for creating magnified images of a microscope slide
CN101072992A (en) 2004-11-12 2007-11-14 卢米尼克斯股份有限公司 Methods and systems for positioning microspheres for imaging
JP2006197172A (en) * 2005-01-13 2006-07-27 Matsushita Electric Ind Co Ltd Black and white/color original discrimination device, black and white/color original discrimination method, and image reader equipped with the same
CN1297944C (en) * 2005-01-26 2007-01-31 北京中星微电子有限公司 A method for detecting image gray scale change
EP3203235A1 (en) 2005-05-23 2017-08-09 Harald F. Hess Optical microscopy with phototransformable optical labels
EP4071458A1 (en) * 2005-09-21 2022-10-12 Luminex Corporation Methods and systems for image data processing
GB0802084D0 (en) 2008-02-05 2008-03-12 Univ Dublin City Microfluidic device for assessing cell surface interactions
JP2012013804A (en) 2010-06-29 2012-01-19 Sony Corp Image processing apparatus, image processing system and image processing method, and program

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