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Non invasive live cell cycle monitoring using quantitative phase imaging and proximal machine learning methods

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Academic year: 2021

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Figure

Fig. 1: Illustration of the QLSI principle. Top : Side view of the interferometer. The light impinging from the left diffracts through a diffraction grating and then interferes on the camera detector
Fig. 2: Features extracted from QPI images of segmented cells.
Fig. 5: The machine learning approach uses the matrix W in the projected k × k space as signature

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