US 12,437,563 B2
Analysis method and analyzer
Shoichiro Asada, Kobe (JP); Konobu Kimura, Kobe (JP); Masamichi Tanaka, Kobe (JP); and Kenichiro Suzuki, Kobe (JP)
Assigned to SYSMEX CORPORATION, Kobe (JP)
Filed by SYSMEX CORPORATION, Kobe (JP)
Filed on Mar. 10, 2022, as Appl. No. 17/691,793.
Claims priority of application No. 2021-040829 (JP), filed on Mar. 12, 2021; application No. 2021-040830 (JP), filed on Mar. 12, 2021; and application No. 2021-040831 (JP), filed on Mar. 12, 2021.
Prior Publication US 2022/0292855 A1, Sep. 15, 2022
Int. Cl. G06V 20/69 (2022.01); G01N 15/1404 (2024.01); G01N 15/1429 (2024.01); G01N 15/1434 (2024.01); G01N 33/49 (2006.01); G01N 35/00 (2006.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01)
CPC G06V 20/698 (2022.01) [G01N 15/1404 (2013.01); G01N 15/1429 (2013.01); G01N 15/1434 (2013.01); G01N 33/49 (2013.01); G01N 33/4915 (2013.01); G01N 35/00871 (2013.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G01N 2035/00891 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30242 (2013.01)] 22 Claims
OG exemplary drawing
 
1. An analysis method for a specimen using an analyzer connected to a host computer, the analysis method comprising:
preparing a measurement sample by mixing the specimen and a reagent in a chamber of the analyzer;
optically interrogating the measurement sample with an optical detector of the analyzer to obtain feature data of individual cells contained in the measurement sample;
analyzing the feature data with a deep learning algorithm trained to output a set of values of probabilities in response to an input of the feature data of the individual cell, wherein each of the values corresponds to one cell type of multiple cell types and the value represents a probability that the individual cell belongs to the corresponding cell type;
generating classification information for the individual cells, wherein the classification information comprises at least following information:
(i) a primary cell type to which the individual cell belongs with the highest probability,
(ii) a secondary cell type to which the individual cell belongs with the second highest probability, and
(iii) the values of probabilities for the primary and secondary cell types;
generating a measurement result of the specimen on the basis of the primary cell type in the classification information;
displaying, on a display part of the analyzer, the measurement result and at least a part of the classification information;
validating the measurement result; and
transmitting, upon the validation, output data to the host computer, wherein the output data includes the measurement result and the classification information from which the information (ii) or the information (iii) is removed.