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公开(公告)号：US09904842B2
公开(公告)日：2018-02-27
申请号：US14654347
申请日：2013-12-19
CPC分类号： G06K9/00147 , G01N15/0227 , G01N15/1434 , G01N15/1475 , G01N2015/144 , G01N2015/1445 , G01N2015/1488 , G06K9/00127 , G06K9/0014 , G06T5/50 , G06T7/0012 , G06T2207/10056 , G06T2207/20084 , H04N13/296
摘要： A particle classifier system and a method of training the system are described. The particle classifier system is suitable for classification of particles in a liquid sample, said particle classifier system comprises—an optical detection assembly comprising at least one image acquisition device with an optical axis, the image acquisition device is configured to acquire images of an image acquisition area perpendicular to said optical axis; —a sample device comprising at least one sample container suitable for holding a sample in liquid form; —a translating arrangement configured to translate said image acquisition area through at least a part of said sample container; —a control system configured to controlling said optical detection assembly and said translating unit to acquire images of a plurality of image acquisition areas; —an image analyzing processing system programmed to analyze said acquired images by a method comprising creating objects (sub-images) of individual particles captured by said acquired images, creating stacks of objects of each individual particle, identifying complete stacks of objects comprising at least one object wherein said particle is in-focus, and two objects wherein said particle is out-of-focus, and determining, for each of said complete stacks of objects, a set of values for a set of features of at least N features, wherein N is larger than or equal to 1, and wherein the determination of said values of said set of features involve data obtained from said at least one object wherein said particle is in-focus, and/or said at least two objects wherein said particle is out-of-focus; and —an artificial intelligent processing system programmed to associate said set of values for said determined set of features for each individual particle to a particle classification.
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公开(公告)号：US10782306B2
公开(公告)日：2020-09-22
申请号：US16064780
申请日：2016-12-22
摘要： The invention relates to a method of determining a concentration of a substance in a cell suspension, said method comprising the following steps: —determining the concentration of the substance by: —using the results of absorption measurements performed at n local sample volumes contained at different average chamber heights of a chamber arrangement comprising the cell suspension and local substance concentration in said respective local sample volumes determined based on said respective absorption measurements; —using a substance concentration model comprising local substance concentration as a function of chamber height, and—determining the substance concentration as the infinite chamber height substance concentration using said substance concentration model and the determined local substance concentrations, wherein n is at least 2, such as at least 3, such as at least 4, wherein, optionally, the cell suspension is whole blood and the substance is Hb and wherein the method further comprises determining cRBC based on the determined Hb concentration and a determined Mean Corpuscular Hemoglobin (MCH). The invention also relates to a system for executing the method.
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公开(公告)号：US10192100B2
公开(公告)日：2019-01-29
申请号：US15886925
申请日：2018-02-02
摘要： A particle classifier system and a method of training the system are described. The particle classifier system is suitable for classification of particles in a liquid sample, said particle classifier system comprises an optical detection assembly comprising at least one image acquisition device with an optical axis, the image acquisition device is configured to acquire images of an image acquisition area perpendicular to said optical axis; a sample device comprising at least one sample container suitable for holding a sample in liquid form; a translating arrangement configured to translate said image acquisition area through at least a part of said sample container; a control system configured to controlling said optical detection assembly and said translating unit to acquire images of a plurality of image acquisition areas; an image analyzing processing system programmed to analyze said acquired images by a method comprising creating objects (sub-images) of individual particles captured by said acquired images, creating stacks of objects of each individual particle, identifying complete stacks of objects comprising at least one object wherein said particle is in-focus, and two objects wherein said particle is out-of-focus, and determining, for each of said complete stacks of objects, a set of values for a set of features of at least N features, wherein N is larger than or equal to 1, and wherein the determination of said values of said set of features involve data obtained from said at least one object wherein said particle is in-focus, and/or said at least two objects wherein said particle is out-of-focus; and an artificial intelligent processing system programmed to associate said set of values for said determined set of features for each individual particle to a particle classification.
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公开(公告)号：US09841593B2
公开(公告)日：2017-12-12
申请号：US14299329
申请日：2014-06-09
CPC分类号： G02B21/367 , G01N15/1434 , G01N15/1475 , G01N17/00 , G01N2015/1445 , G01N2015/1452 , G02B21/002 , G06K9/00134 , G06T7/0012 , G06T2207/10016 , G06T2207/10061 , G06T2207/30024 , G06T2207/30101 , H04N13/189 , H04N13/239 , H04N13/296
摘要： An apparatus for obtaining a plurality of images of a sample includes a sample device suitable for holding a liquid sample; a first optical detection assembly including a first image acquisition device, the first optical detection assembly having an optical axis and an object plane, the object plane including an image acquisition area from which electromagnetic waves can be detected as an image by the first image acquisition device; one translation unit arranged to move the sample device and the first optical detection assembly relative to each other; and an image illumination device, wherein the apparatus is arranged to move the sample device and the first optical detection assembly relative to each other along a scanning path, which defines an angle theta relative to the optical axis, wherein theta is in the range of about 0.3 to about 89.7 degrees.
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公开(公告)号：US10549480B2
公开(公告)日：2020-02-04
申请号：US16348553
申请日：2017-11-17
摘要： The invention is about an ultrasonic welding-based microfluidic device. It is mainly made of a first element and a second element welded one to the other via at least one structure (10, 10′). The structure (10, 10′) comprises an elongated welded portion for said welding, a welding channel (12, 12′) extending between the first and second elements and along one side of the welded portion, and a draining channel (13) communicating with the welding channel (12, 12′) and the microfluidic path (20, 20′) of the device. The invention is further about a method of manufacturing such a device.
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公开(公告)号：US10430640B2
公开(公告)日：2019-10-01
申请号：US16231650
申请日：2018-12-24
摘要： A particle classifier system and a method of training the system are described. The particle classifier system is suitable for classification of particles in a liquid sample, said particle classifier system comprises an optical detection assembly comprising at least one image acquisition device with an optical axis, the image acquisition device is configured to acquire images of an image acquisition area perpendicular to said optical axis; a sample device comprising at least one sample container suitable for holding a sample in liquid form; a translating arrangement configured to translate said image acquisition area through at least a part of said sample container; a control system configured to controlling said optical detection assembly and said translating unit to acquire images of a plurality of image acquisition areas; an image analyzing processing system programmed to analyze said acquired images by a method comprising creating objects (sub-images) of individual particles captured by said acquired images, creating stacks of objects of each individual particle, identifying complete stacks of objects comprising at least one object wherein said particle is in-focus, and two objects wherein said particle is out-of-focus, and determining, for each of said complete stacks of objects, a set of values for a set of features of at least N features, wherein N is larger than or equal to 1, and wherein the determination of said values of said set of features involve data obtained from said at least one object wherein said particle is in-focus, and/or said at least two objects wherein said particle is out-of-focus; and an artificial intelligent processing system programmed to associate said set of values for said determined set of features for each individual particle to a particle classification.
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