Polychromatic digital holographic microscopy (P-DHM) has demonstrated its capacity to generate highly denoised optical path difference images, thereby enabling the label-free visualization of fine cellular structures, such as the dendritic arborization within neuronal cells in culture. So far, however, the sample must remain more or less stationary since P-DHM is performed manually, i.e. all actions are carried out sequentially over several minutes. In this paper, we propose a fully automated, robust, and efficient management of the acquisition and reconstruction of time series of polychromatic hologram sets, transforming P-DHM into time-lapse P-DHM. Experimental results have demonstrated the ability of the proposed time-lapse P-DHM implementation to non-invasively and quantitatively reveal the fine structure and dynamics of living cells.
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Haouat et al. (2024) studied this question.
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