Pycro-Manager: open-source software for customized and reproducible microscope control
Nature methods, 2021•nature.com
To the Editor—Cutting-edge innovations in biological microscopy are increasingly blurring
the line between data acquisition and data analysis. Computational microscopy and
machine-learning-based methods take this paradigm to an extreme, often producing raw
measurements that are not human-interpretable without postprocessing 1–3. Furthermore,
new data-adaptive imaging methods rely on data processing during acquisition to actively
control various hardware settings of the microscope.
the line between data acquisition and data analysis. Computational microscopy and
machine-learning-based methods take this paradigm to an extreme, often producing raw
measurements that are not human-interpretable without postprocessing 1–3. Furthermore,
new data-adaptive imaging methods rely on data processing during acquisition to actively
control various hardware settings of the microscope.
To the Editor—Cutting-edge innovations in biological microscopy are increasingly blurring the line between data acquisition and data analysis. Computational microscopy and machine-learning-based methods take this paradigm to an extreme, often producing raw measurements that are not human-interpretable without postprocessing 1–3. Furthermore, new data-adaptive imaging methods rely on data processing during acquisition to actively control various hardware settings of the microscope.
nature.com
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