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Phase contrast microscopy is a white-light optical microscopy technique that relies on sample-induced phase changes in illumination light to generate images with more information than provided by sample-induced intensity changes. Phase information is mixed with intensity information in conventional phase-contrast microscopy, whereas quantitative phase-contrast microscopy displays only the phase information.
A parameterized physical model that uses unpaired datasets for adaptive holographic imaging was published in Nature Machine Intelligence in 2023. Zhang and colleagues evaluate its performance and extend it to non-perfect optical systems by integrating specific optical response functions.
The authors use deep learning to detect and segment unlabeled and unaltered protein aggregates in living cells from transmitted-light images. The method provides a way to quantitatively study protein aggregation dynamics in a simple, fast and accurate way.
A clever extension to a classic phase-contrast microscope allows speckle-free three-dimensional quantitative phase imaging of living cells in a tomographic imaging mode.
Atomic-resolution differential phase-contrast imaging using aberration-corrected scanning transmission electron microscopy now provides a sensitive probe of the electric field associated with individual atoms.
