Unsupervised discovery of dynamic cell phenotypic states from transmitted light movies

Unsupervised discovery of dynamic cell phenotypic states from transmitted light movies

Identification of cell phenotypic states within heterogeneous populations, along with elucidation of their switching dynamics, is a central challenge in modern biology. Conventional single-cell analysis methods typically provide only indirect, static phenotypic readouts. Transmitted light images, on...

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Bibliographic Details
Main Authors: Becker, P.S (Author), Chien, S. (Author), Dai, J. (Author), Kueh, H.Y (Author), Monnat, R.J (Author), Nguyen, P. (Author)
Format: Article
Language:English
Published: Public Library of Science 2021
Subjects:
acute myeloid leukemia
acute myeloid leukemia cell line
adult
algorithm
Algorithms
Article
blood cell
Blood Cells
cell structure
cell subpopulation
cell tracking
classification
classification algorithm
convolutional neural network
cytology
deep learning
human
human cell
Humans
image processing
Image Processing, Computer-Assisted
image segmentation
Leukemia, Myeloid, Acute
light
Light
live cell imaging
microscopy
Microscopy
pathology
phenotype
Phenotype
procedures
single cell analysis
Single-Cell Analysis
time lapse imaging
Time-Lapse Imaging
unsupervised machine learning
Unsupervised Machine Learning
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Internet

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