US 11,900,600 B2
Methods of analyzing microscopy images using machine learning
John A. Stamatoyannopoulos, Seattle, WA (US); Shreeram Akilesh, Seattle, WA (US); Alexander Muratov, Seattle, WA (US); Wouter Meuleman, Seattle, WA (US); and William Kerwin, Seattle, WA (US)
Assigned to Altius Institute for Biomedical Sciences, Seattle, WA (US)
Filed by Altius Institute for Biomedical Sciences, Seattle, WA (US)
Filed on Oct. 10, 2022, as Appl. No. 18/045,342.
Application 18/045,342 is a continuation of application No. 16/630,090, granted, now 11,501,429, previously published as PCT/US2018/042964, filed on Jul. 19, 2018.
Claims priority of provisional application 62/534,679, filed on Jul. 19, 2017.
Prior Publication US 2023/0274423 A1, Aug. 31, 2023
Int. Cl. G06T 7/00 (2017.01); G06N 20/00 (2019.01); G16B 40/30 (2019.01); G16B 40/20 (2019.01)
CPC G06T 7/0012 (2013.01) [G06N 20/00 (2019.01); G16B 40/20 (2019.02); G16B 40/30 (2019.02); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for characterizing a population of cells, the method comprising:
a) acquiring a series of one or more images of a population of cells, wherein at least one image of the series comprises an image of one or more cells; and
b) processing the series of one or more images using a statistical or machine learning algorithm, wherein the statistical or machine learning algorithm generates a cell characterization data set that comprises a basis representation of one or more key attributes of cells within the population of cells,
wherein the statistical or machine learning algorithm comprises an unsupervised machine learning algorithm, and wherein the unsupervised machine learning algorithm comprises an artificial neural network, an association rule learning algorithm, a hierarchical clustering algorithm, a cluster analysis algorithm, a matrix factorization approach, a dimensionality reduction approach, or any combination thereof.