US 12,230,023 B2
Analysis device
Sadao Ota, Tokyo (JP); Issei Sato, Tokyo (JP); Katsuhito Fujiu, Tokyo (JP); Satoko Yamaguchi, Tokyo (JP); Kayo Waki, Tokyo (JP); Yoko Itahashi, Tokyo (JP); and Ryoichi Horisaki, Osaka (JP)
Assigned to The University of Tokyo, Tokyo (JP); and Osaka University, Osaka (JP)
Filed by The University of Tokyo, Tokyo (JP); and OSAKA UNIVERSITY, Osaka (JP)
Filed on Nov. 16, 2023, as Appl. No. 18/511,920.
Application 18/511,920 is a continuation of application No. 18/059,846, filed on Nov. 29, 2022, granted, now 11,861,889.
Application 18/059,846 is a continuation of application No. 17/351,117, filed on Jun. 17, 2021, granted, now 11,542,461, issued on Jan. 3, 2023.
Application 17/351,117 is a continuation of application No. 15/771,180, granted, now 11,098,275, issued on Aug. 24, 2021, previously published as PCT/JP2016/082089, filed on Oct. 28, 2016.
Claims priority of provisional application 62/372,321, filed on Aug. 9, 2016.
Claims priority of application No. 2015-212356 (JP), filed on Oct. 28, 2015.
Prior Publication US 2024/0303980 A1, Sep. 12, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G01N 15/14 (2024.01); C12M 1/34 (2006.01); G01N 15/1404 (2024.01); G01N 15/1429 (2024.01); G01N 15/1434 (2024.01); G01N 21/01 (2006.01); G01N 21/27 (2006.01); G01N 21/64 (2006.01); G01N 21/65 (2006.01); G06F 18/21 (2023.01); G06F 18/28 (2023.01); G06V 10/772 (2022.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01); G06V 20/69 (2022.01); G01N 15/10 (2006.01)
CPC G06V 10/82 (2022.01) [C12M 1/34 (2013.01); G01N 15/14 (2013.01); G01N 15/1404 (2013.01); G01N 15/1429 (2013.01); G01N 15/1434 (2013.01); G01N 15/1459 (2013.01); G01N 15/147 (2013.01); G01N 21/01 (2013.01); G01N 21/27 (2013.01); G01N 21/64 (2013.01); G01N 21/65 (2013.01); G06F 18/2178 (2023.01); G06F 18/28 (2023.01); G06V 10/772 (2022.01); G06V 10/7784 (2022.01); G06V 20/698 (2022.01); G01N 2015/1006 (2013.01); G01N 2015/1413 (2013.01); G01N 2015/1415 (2013.01); G01N 2015/145 (2013.01); G06F 2218/12 (2023.01)] 18 Claims
OG exemplary drawing
 
1. A method, comprising:
(a) providing one or more flow cytometers comprising a flow path and a light receiving unit, wherein the light receiving unit comprises one or more sensors;
(b) flowing one or more objects through the flow path of the one or more flow cytometers;
(c) irradiating the one or more objects with a structured illumination pattern as the one or more objects move relative to the structured illumination pattern in a light irradiation region, wherein the light irradiation region is located on at least a portion of the flow path in which the one or more objects flow through;
(d) detecting at least one electromagnetic wave from the one or more objects using the one or more sensors, wherein the one or more objects comprises at least one target object;
(e) converting the least one electromagnetic wave into one or more time-series electrical signals using the light receiving unit; and
(f) analyzing the one or more time-series electrical signals using a machine learning classification model to obtain one or more classification results.